ICINCO 2018 Abstracts

Area 1 - Industrial Informatics

Full Papers

Paper Nr:	25
Title:	Can Artificial Potentials Suit for Collision Avoidance in Factory Floor? - A Case Study of Harmonic Machine-machine Coexistence
Authors:	Josias G. Batista, José L. N. da Silva and George A. P. Thé
Abstract:	Despite the existence of well-known approaches for collision prevention in the robotics literature, in present days the use of manipulators in fabrication processes still relies on safe-zone delimitations, which ultimately limits automation flexibility. In the present work, we consider going over that paradigm by discussing what if mobile agents of the fabrication process, i.e., robots could share the same space. In doing that study, the very classical approach based on artificial potentials for collision prevention are preferred over modern choices. On the basis of a hypothetical pick-&-place task experiment, results revealed efficient accomplishment in some of the considered scenarios.
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Paper Nr:	84
Title:	Modelling and Simulation of High-viscosity, Non Iso-thermal Fluids with a Free Surface
Authors:	Dimitri Harder, Edmond Skeli and Dirk Weidemann
Abstract:	With the aim of using efficient control and/or diagnostic methods, more and more companies in the process engineering industry are using mathematical models to describe the underlying physical processes in sufficient detail. Against this background, the modeling and simulation of the behaviour of a non-isothermal, highly viscous fluid flow is examined in this paper. The behaviour of the fluid is decribed by a system of partial differential equations, which includes the incompressible Navier-Stokes equations as well as the thermal energy equation. With regard to the numerical calculation of the process variables, a combination of the Marker and Cell (MAC) method and a temperature calculation on a curvilinear grid is presented. The MAC method is used to identify the free surface by inserting particles without masses over the initialized fluid area and moving them with the calculated velocities. A characteristic feature of the typical use of the MAC method is that the defining partial differential equations are discretized spatially on a rectangular grid. However, this leads to the problem that a large part of the grid nodes lies within the obstacles which are surrounded by the fluid. In the present model, on the other hand, a curvilinear grid is used. The main advantage of this is that the outer grid nodes lie directly on the surrounding obstacles, resulting in a reduced system of differential-algebraic equations.
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Short Papers

Paper Nr:	57
Title:	Optimal Coordination of Robot Motions with Positioner and Linear Track in a Fiber Placement Workcell
Authors:	Jiuchun Gao, Anatol Pashkevich, Marco Cicellini and Stéphane Caro
Abstract:	The paper proposes a methodology for optimal coordination of motions in robotic systems with multiple redundant actuators. In contrast to our previous results dealing with a single redundant axis, the extended technique is proposed allowing the robot, positioner and linear track to be actuated simultaneously in order to reduce the total processing time. The developed technique transforms the original continuous problem into a discrete one where the desired time-optimal motions are presented as a shortest path on the task graph satisfying the problem-specific acceleration and velocity constraints imposed on the joint coordinates. The desired time optimal motions are generated using enhanced dynamic programming algorithm that considers both of these constraints. Two case studies are presented to demonstrate efficiency of the approach and evaluate benefits of simultaneous actuation of all robotic system axes.
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Paper Nr:	107
Title:	Embedded Agent based on Cyber Physical Systems: Architecture, Hardware Definition and Application in Industry 4.0 Context
Authors:	Mario Ricardo Nascimento Marques Junior, Braian Konzgen Maciel, Gabriel M. Balota, Renan T. Fonseca, Manuel Simosa, Henrique S. Conceição, Eder Mateus Nunes Gonçalves and Silvia Silva da Costa Botelho
Abstract:	Industry 4.0 is promoting a new Industrial Revolution through the application of computer and communication technologies for the construction of Cyber Physical Systems (CPS), which can be considered a key component for the development of this new revolution. In this context, this article proposes to implement an architecture for embedded intelligent agents based on CPS. For this, it is proposed a classification of hardware suitable for boarding this agent. Through this classification a device and initial testing of the agent is selected using the MTConnect standard, which currently presents itself as a potentially efficient standard for this application given the guarantees of some communication requirements. The initial tests presented satisfactory results in the system against the requirements of communication, processing and storage. In addition, the benefits of the proposed architecture over traditional automation systems are presented. Finally, the possible scenario for validation of this architecture is presented.
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Paper Nr:	125
Title:	Taguchi Loss Function to Minimize Variance and Optimize a Flexible Manufacturing System (FMS): A Six Sigma Approach Framework
Authors:	Wa-Muzemba Anselm Tshibangu
Abstract:	This paper analyzes a flexible manufacturing system (FMS) and presents a new scheme to find the optimal operational parameters settings of two of the mostly used performance measures in assessing manufacturing and production systems, namely the throughput rate (TR) and the mean flow time (MFT). The scheme uses an off-line model that combines discrete-event simulation, robust design principles and mathematical analysis to uncover the optimal settings. The research suggests a two-level optimization procedure that uses an empirical process followed by an analytical technique. In a first level, the empirical approach serves to derive the near-optimal values of the two individual performance measures of interest. These values are then used as targets in the second level of the optimization procedure in which, a Taguchi quality loss function (QLF) is applied to the FMS mathematical model derived through simulation-meta-modeling to find the optimal parameter settings. As advocated in Six Sigma Methodology the optimization of the modeled system is implemented and achieved through a minimization of the performance variation followed by an optimal adjustment of the performance’s mean if necessary, in order to minimize the overall loss incurred due to the deviation of the mean from target.
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Paper Nr:	132
Title:	LoggerBIT: An Optimization of the OpenLog Board for Data Logging with Low Cost Hardware Platforms for Biomedical Applications
Authors:	Margarida Reis and Hugo Plácido da Silva
Abstract:	Low cost hardware and open source software tools specialized in biomedical applications have recently seen a significant growth both in popularity and diversity. Within the current landscape of such tools, BITalino is increasingly used by students and professors for educational activities and prototyping, due to its modular design and flexibility. However, there is currently no user-friendly way of storing data locally without setting up a wireless connection to a receiver unit (e.g. a computer or smartphone). This poses a problem, especially in uses cases where ambulatory data acquisition is needed. In this paper we present the LoggerBIT, a data logging block to enable data recording onto a microSD card in biomedical development toolkits, without requiring a connection to a receiver nor any particular programming or electronics skills to setup. Our work builds upon the OpenLog serial data logger, to which multiple optimisations were made in terms of hardware and firmware, overcoming limitations preventing its use in high data throughput applications. Our LoggerBIT approach is suitable for high-speed data recording, with results showing that it can log data of up to 4 analog channels at 1000 Hz for 24 hour periods without loss of packets, and from all analog channels with minimal data loss. This work contributes to the state-of-the-art with a comprehensive description and validation of the block, and with a set of supporting tools released in open source, thus available for the biomedical engineering community at large.
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Paper Nr:	139
Title:	Towards a Tool-based Methodology for Developing Software for Dynamic Robot Teams
Authors:	Roland Glück, Alwin Hoffmann, Ludwig Nägele, Andreas Schierl, Wolfgang Reif and Heinz Voggenreiter
Abstract:	Considering initiatives like Industry 4.0 or the Industrial Internet of Things, robots will play an important role in intelligent factories, producing highly customized products with high variability and in small lot sizes. In this setting, complexity of planning and programming such robotic applications grows due to the drastic increase in flexibility, performance and robustness required. In this paper, we propose a tool-supported methodology for the development of control software for dynamically forming multi-functional robot teams. The main challenges for achieving this overall goal are modeling of robot team skills, techniques for automatically deriving process steps from the products’ construction plans, finding allocations of those steps to possible robot teams with compatible skills and calculating collision-free execution schedules with a high degree of parallelization to improve cycle times. The proposed approach integrates process experts and automation experts on all levels. Two case studies will serve as test beds to the developed approach: production of carbon-fiber reinforced polymers and assembly of furniture.
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Paper Nr:	152
Title:	Using Modelling and Simulation as a Service (MSaaS) for Facilitating Flexibility-based Optimal Operation of Distribution Grids
Authors:	Moritz Stüber, Lukas Exel and Georg Frey
Abstract:	In this contribution, initial results of a research project on modelling and simulation as a service (MSaaS) within the context of optimal operation of distribution grids by exploiting flexibility are summarized. Based on a brief description of service-oriented architecture (SOA), definitions and key aspects of MSaaS as well as open conceptual and technical challenges are outlined. Some specific aspects and challenges are then related to a possible application: a service that predicts the flexibility that a power-to-heat system can offer is implemented as an instance of MSaaS. The calculations are based on the current state of the system and a model defined in the equation-based, object-oriented language Modelica, as well as historical data when available. Thereby, an accurate and reliable representation of the flexiblity becomes available that facilitates its use for system balancing, energy market participation and grid operations. This functionality is exposed through a representational state transfer (REST)-based service interface, designed to allow for the straightforward integration with existing systems and other virtual resources. The service architecture and initial results of the implementation are described.
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Paper Nr:	178
Title:	Root Cause Analysis of Deep Drawing Processes with Superimposed Low-Frequency Vibrations on Servo-Screw Presses - A Practical Research on Predictability in Simulation
Authors:	André Sewohl, Sebastian Kriechenbauer, Peter Müller, Holger Schlegel and Dirk Landgrebe
Abstract:	In the area of sheet metal forming, modelling and simulation of deep drawing processes with finite-element analysis are an essential method for an accurate process design and the production engineering of complex parts. The continuous evaluation and qualification of simulation strategies improve the predictability and help to understand complex forming processes. In order to fulfil the constantly growing requirements on product quality and part variety, dimensional accuracy as well as energy and cost efficiency, it is necessary to achieve reasonable forecasting results and optimal parameters. However, the development of enhanced deep drawing techniques supported by vibrations is in general just beginning. Currently, prediction of process parameters as well as the knowledge about effects and coherences of highly dynamic processes with flexible kinematics are insufficient. In this paper, an approach for improvements in simulation of a new technology for deep drawing on servo-screw presses called cushion-ram pulsation is presented. Numerical and experimental model tests in special constructed set-ups have to be performed to determine particular forces. Sensitivity based methods help to identify significant process parameters of complex forming processes with superimposed vibrations. The evaluation of these parameters allows the development of specific meta-models which approximate the behavior in the simulation.
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Paper Nr:	193
Title:	Quality Control Monitoring by using Artificial Neural Networks for an Iberian Ham Industry
Authors:	J. A García-Esteban, Belén Curto, Vidal Moreno and Beatriz Martínez
Abstract:	The iberian ham is a high valued product, due to this fact, it is very important to offer to the costumer a high quality food product and to ensure its organoleptic properties. Producers have to evaluate, periodically, its sensorial attributes by a professional tasting panel. Due to high elevated organizational and economics costs, in addition to, the sensory fatigue and the subjectivity of the panel members, only a few product lots are sampled. In this paper is proposed a cloud manufacturing based platform to monitor the quality of Iberian ham. The success of this solution is based on cooperation and data exchange between the main agents involved in the process: quality manager, professional tasters, production manager, inspection authorities, etc. Intelligent algorithms have been embedded into the cloud monitoring platform to predict the ham sensory properties, using the Near InfraRed Spectroscopy data from the product samples as input. The key feature of the solution is that the sensory analysis is performed without gathering routinely a professional tasting panel, but the solution also allows to the quality manager, with advanced visualization techniques, to monitor what is the merit figure related with a specific type of ham or shoulder. Another important aspect of the solution is that, due to the huge amount of data coming from the elaboration process itself are available is possible to fine-tune continuously the machine-learning algorithms to the particular producer and use them intelligently to increase the competitiveness.
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Paper Nr:	102
Title:	Automatic Planning of Manufacturing Processes using Spatial Construction Plan Analysis and Extensible Heuristic Search
Authors:	Ludwig Nägele, Andreas Schierl, Alwin Hoffmann and Wolfgang Reif
Abstract:	When automating small-batch manufacturing processes, the time spent for process planning and robot programming becomes more important. This paper proposes an automated process including construction plan analysis, process planning and execution to reduce the amount of manual work required. The process starts by analyzing the structure of the desired product and deriving required process step results, then uses heuristic search to find possible production steps and task assignments, and concludes by simulating or executing the resulting production plan. The approach is evaluated on a case study with a simulated robot automatically building different LEGO R DUPLO R!structures starting from a 3D model defining the desired product.
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Area 2 - Intelligent Control Systems and Optimization

Full Papers

Paper Nr:	19
Title:	Optimal Time-sampling Problem in a Statistical Control with a Quadratic Cost Functional - Analytical and Numerical Approaches
Authors:	Valery Y. Glizer and Vladimir Turetsky
Abstract:	We consider the problem of constructing an optimal time-sampling for a Statistical Process Control (or, briefly, Statistical Control (SC)). The aim of this time-sampling is to minimize the expected loss, caused by a delay in the detection of an undesirable process change. We study the case where this loss is a quadratic functional of the sampling time-interval. This problem is modeled by a nonstandard calculus of variations problem. We propose two approaches to the solution of this calculus of variations problem. The first approach is based on its equivalent transformation to an optimal control problem. The latter is solved by application of the Pontryagin’s Maximum Principle, yielding an analytical expression for the optimal time-sampling in the SC. The second approach uses a discretization of the calculus of variations problem, resulting in a finite dimensional quadratic optimization problem. Solution of the latter provides a suboptimal time-sampling in the SC. The time-samplings, obtained by these two approaches, are compared to each other in numerical examples.
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Paper Nr:	26
Title:	Variable Support Control for the Wave Equation - A Multiplier Approach
Authors:	Antonio Agresti, Daniele Andreucci and Paola Loreti
Abstract:	We study the controllability of the multidimensional wave equation in a bounded domain with Dirichlet boundary condition, in which the support of the control is allowed to change over time. The exact controllability is reduced to the proof of the observability inequality, which is proven by a multiplier method. Besides our main results, we present some applications.
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Paper Nr:	34
Title:	Towards a Knowledge-driven Maintenance Support System for Manufacturing Lines
Authors:	E. Garcia, N. Montes and M. Alacreu
Abstract:	This paper presents how to design a Knowledge-driven Maintenance Support System (MSS) to prognostic breakdowns in production lines and how it affects to the production rate. The system is based on the sub-cycle time monitorization and how the cycle time variability of machine parts can be used as a deterioration indicator that could describe the dynamic of the failure for the machine parts. For this proposal, a novel model based on mini-terms and micro-terms introduced in our previous work as a machine subdivision is used. A mini-term subdivision can be selected by the expert team for several reasons, the replacement of a machine part or simply to analyze the machine more adequately. (A micro-term is a component from a mini-term and it can be as small as the user wishes. Without loss of generality, the paper focuses its attention on a welding line at Ford Motor Company located at Almusafes (Valencia) where a welding unit was isolated and tested for some particular pathologies. The cycle time of each mini-term is measured by changing the deteriorated components in the cycle time. The deterioration of the parts (a proportional valve, a cylinder, an electrical transformer, the robot speed and the loss of pressure) are tested within the range of normal production, which is the range that cannot be detected by alarms or maintenance workers but when the change point is occured. The statistical analysis of the data obtained in the experiments allows us to define the rules that govern the decisions for the real-time Knowledge-driven MSS. This analysis and the welding line simulation also allows us to know the loss of productivity when the change point occurs. In the worst case, the welding line reduces their production rate almost 40%.
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Paper Nr:	40
Title:	Nonlinear Control Structure Design using Grammatical Evolution and Lyapunov Equation based Optimization
Authors:	Elias Reichensdörfer, Dirk Odenthal and Dirk Wollherr
Abstract:	A new method for the automated synthesis of nonlinear control laws for nonlinear control systems using grammatical evolution is presented. The controller structure, its parameterization and a quadratic Lyapunov function are the result of a nonlinear, nonconvex optimization process. Evolutionary algorithms based on grammatical evolution are used to find candidates for the control law. These are evaluated using a fitness function incorporating eigenvalue specifications on the linearized closed loop system and bounds on the control input signals. The guaranteed domain of attraction subject to the closed loop performance and stability specifications is maximized by evaluating the solution of the Lyapunov equation on the nonlinear system. The method is tested on two different control systems that contain different types of nonlinearities. The results show that the proposed approach is capable of outperforming state of the art methods by providing stronger stability guarantees and/or better closed loop performance while making less restrictive assumptions.
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Paper Nr:	96
Title:	Numerical Investigation of Newton’s Method for Solving Discrete-time Algebraic Riccati Equations
Authors:	Vasile Sima and Peter Benner
Abstract:	A Newton-like algorithm and some line search strategies for solving discrete-time algebraic Riccati equations are discussed. Algorithmic and implementation details incorporated in the developed solver are described. Some numerical results of an extensive performance investigation on a large collection of examples are summarized. These results often show significantly improved accuracy, measured in terms of normalized and relative residuals, in comparison with the state-of-the-art MATLAB function. The new solver is strongly recommended for improving the solutions computed by other solvers.
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Paper Nr:	119
Title:	Water Asset Management Strategy based on Predictive Rainfall/Runoff Model to Optimize the Evacuation of Water to the Sea
Authors:	Baya Hadid and Eric Duviella
Abstract:	Hydrographical networks are large scale systems that are used to answer to the Human uses. They are impacted by extreme events that should be bigger due to climate change. By focusing on extreme rainy events, the amount of water in excess has to be dispatched on all the network to avoid flood, and then rejected to the sea heeding the tides. Pumps can also be used to reject the water to the sea but they lead to big operating cost. To deal with this challenging issue, the modelling tools and the water asset management strategies that have been recently proposed are adapted and improved in this paper. They consist in an integrated model, a flow-based network and a quadratic optimization based on constrains. The efficiency of this water management strategy requires an accurate predictive rainfall/runoff model. It is highlighted by considering a realistic case study that is also used to describe all the methodology step.
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Paper Nr:	164
Title:	Quadcopter Control Approaches and Performance Analysis
Authors:	Vasco Brito, Alexandre Brito, Luis Brito Palma and Paulo Gil
Abstract:	This article presents the kinematic and dynamic model of a X8 quadcopter, as well as control methodologies based on the PID controller and Sliding Mode Controller. The main contributions are centered on the controllers tuning based on particle swarm optimization algorithm and on the controllers performance comparison for nominal operation and for faulty situations. In order to show the overall performance, simulation results for trajectory and orientation tracking control are presented.
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Paper Nr:	177
Title:	Automatic Detection of Subassemblies for Disassembly Sequence Planning
Authors:	Yongjing Wang, Feiying Lan, Duc Truong Pham, Jiayi Liu, Jun Huang, Chunqian Ji, Shizhong Su, Wenjun Xu, Quan Liu and Zude Zhou
Abstract:	Disassembly, the first process in remanufacturing, is labour-intensive due to the conditions of end-of-life products returned for remanufacture. Robotic disassembly is an attractive alternative to manual disassembly but robotic systems cannot plan disassembly sequences automatically and manual planning is still required. Several planning methods have been proposed to take away removable components sequentially. However, those methods do not work when it is required to break an assembly into subassemblies. This paper proposes a method for automatic detection of subassemblies. The approach starts with using an assembly matrix and simple logic gates to generate a contact matrix and a relation matrix. The paper details new algorithms used to detect subassemblies through manipulating the two matrices.
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Short Papers

Paper Nr:	24
Title:	Autonomous Trail Following using a Pre-trained Deep Neural Network
Authors:	Masoud Hoveidar-Sefid and Michael Jenkin
Abstract:	Trails are unstructured and typically lack standard markers that characterize roadways; nevertheless, trails can provide an effective set of pathways for off-road navigation. Here we approach the problem of trail following by identifying the deviation of the robot from the heading angle of the trail through the refinement of a pretrained Inception-V3 (Szegedy et al., 2016a) Convolutional Neural Network (CNN) trained on the ImageNet dataset (Deng et al., 2009). A differential system is developed that uses a pair of cameras each providing input to its own CNN directed to the left and the right that estimate the deviation of the robot with respect to the trail direction. The resulting networks have been successfully tested on over 1 km of different trail types (asphalt, concrete, dirt and gravel).
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Paper Nr:	43
Title:	A Fault-Tolerant Sensor Reconciliation Scheme based on Self-Tuning LPV Observers
Authors:	Hamid Behzad, Alessandro Casavola, Francesco Tedesco, Mohammad Ali Sadrnia and Gianfranco Gagliardi
Abstract:	This paper presents a fault-tolerant sensor reconciliation scheme for systems equipped with a redundant number of possibly faulty ”physical” sensors. The reconciliator is in charge to discover on-line, at each time instant, the faulty physical sensors, if any, and exclude their measures from the generation of the ”virtual” sensors, which, on the contrary, are supposed to be always healthy and suitably usable for control purposes without requiring the reconfiguration of the nominal control law. Amongst many, the solution proposed here is based on the use of a Linear Parameter Varying Luenberger Observers (LPV-LU) able to estimate both state, bias fault and loss of effectiveness fault. Such information is used to self adapting the parameters of the LPV representation. For simplicity, the sensor faults here considered are limited to variation of sensors’ gain and offset values. The scheme is fully described and all of its properties investigated and proved. Finally, a simulation example is reported in details to show the effectiveness of the scheme.
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Paper Nr:	67
Title:	Visual Inspection of Storm-Water Pipe Systems using Deep Convolutional Neural Networks
Authors:	Ruwan Tennakoon, Reza Hoseinnezhad, Huu Tran and Alireza Bab-Hadiashar
Abstract:	Condition monitoring of storm-water pipe systems are carried-out regularly using semi-automated processors. Semi-automated inspection is time consuming, expensive and produces varying and relatively unreliable results due to operators fatigue and novicity. This paper propose an innovative method to automate the storm-water pipe inspection and condition assessment process which employs a computer vision algorithm based on deep-neural network architecture to classify the defect types automatically. With the proposed method, the operator only needs to guide the robot through each pipe and no longer needs to be an expert. The results obtained on a CCTV video dataset of storm-water pipes shows that the deep neural network architectures trained with data augmentation and transfer learning is capable of achieving high accuracies in identifying the defect types.
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Paper Nr:	70
Title:	Overseer: A Multi Robot Monitoring Infrastructure
Authors:	Felipe Roman, Alexandre Amory and Renan Maidana
Abstract:	In this paper, we present a lightweight runtime monitoring system for Multi Robot Systems, intended to supervise and identify the state of a team of robots. It integrates the Nagios IT monitoring tool and the ROS robotic middleware without any additional software at the robot side. The experimental results demonstrate that the proposed monitoring system has a negligible performance impact on the robot, and the monitoring server can easily support hundreds or even thousands of monitored robots.
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Paper Nr:	72
Title:	LSHADE Algorithm with a Rank-based Selective Pressure Strategy for the Circular Antenna Array Design Problem
Authors:	Shakhnaz Akhmedova, Vladimir Stanovov and Eugene Semenkin
Abstract:	A new algorithm called LSHADE-RSP, which is based on a modification of the Differential Evolution technique, namely the LSHADE algorithm, with a rank-based selective pressure strategy, is presented in this paper. The basic idea of the proposed approach LSHADE-RSP consists in the adaptation of its mutation strategy, DE/current-to-pbest/1, using the linear rank-based selective pressure. LSHADE-RSP is built to tackle complex high-dimensional global optimization problems, and firstly it has been successfully tested on the CEC 2018 benchmark functions. Then the LSHADE-RSP was used for solving a real-life engineering global optimization problem, more specifically, the circular antenna array design problem. The objective of the stated problem is to vary the current and phase excitations of the antenna elements and try to suppress side-lobes, minimizing beam width, and to achieve null control at the desired directions. From the obtained results, the workability and usefulness of the new approach were confirmed. In addition, it can be concluded that the proposed optimization algorithm demonstrates competitive results in comparison with most alternative algorithms, thus, LSHADE-RSP can be recommended for solving optimization problems instead of them.
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Paper Nr:	95
Title:	Artificial Neural Networks as a Tool for Recognition of Movements by Electroencephalograms
Authors:	Semen A. Kurkin, Elena N. Pitsik, Vyacheslav Yu. Musatov, Anastasia E. Runnova and Alexander E. Hramov
Abstract:	Recognition of human brain activity associated with imaginary or real movements is a complex task that requires an accurate and conscious choice of analysis approach. Recent researches revealed the great potential of machine learning algorithms for electroencephalography data analysis due to the ability of these methods to establish nonlinear and nonstationary correlations, and the most attention is focused on artificial neural networks (ANNs). Here, we introduce the ANN-based method for recognition and classification of patterns in electroencephalograms (EEGs) associated with imaginary and real movements of untrained volunteers. In order to get the fastest and the most accurate classification performance of multichannel motor imagery EEG-patterns, we propose our approach to selection of appropriate type, topology, learning algorithm and other parameters of neural network. We considered linear neural network, multilayer perceptron, radial basis function network and support vector machine. We revealed that appropriate quality of recognition can be obtained by using particular groups of electrodes according to extended international 10−10 system. Besides, pre-processing of EEGs by low-pass filter can significantly increase the classification performance. Obtained results provide better insight on neural networks potential for integration in brain-computer interfaces that are based on EEG patterns recognition.
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Paper Nr:	98
Title:	Forecasting the Class of Daily Clearness Index for PV Applications
Authors:	Giuseppe Nunnari
Abstract:	This paper deals with the problem of forecasting the class of the daily clearness index which can be relevant for PV applications. A large number of solar stations, publicly available, was processed by using five different approaches, namely, the feed-forward neural networks, the Hidden Markov models, the Naive-Bayes models, the Surrogate models and the Persistent models. Experimental results show that one-day ahead forecasting of the class of daily clearness can be reliable performed in a 2-class framework and with less accuracy in a 3-class framework. Furthermore, for this purpose, the HMM approach is recommended among the considered ones. The global performance of the class prediction models, evaluated by calculating the average confusion rate (CR), showed that using HMM models provide CR ≤ 0.3 for 2-class clustering classes, while, for the 3-class framework it rises to 0.35.
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Paper Nr:	113
Title:	Nonlinear Model Predictive Control based Particle Swarm Optimization for Treating Lower Uniray Tract Dysfunction
Authors:	Jean Thomas
Abstract:	Finding a treatment of neurologic Lower Urinary Tract (LUT) has received a good attention by the medical society. Neurologic LUT is a disease that affects the urinary bladder due to mostly central nervous system or peripheral nerves malfunctions. Many treatment approaches have already been introduced to patients and many others are still under investigation. Examples of the existing ones are different types of medications, surgery approaches and open loop Electrical-stimulatory therapies while example of the under research is closed loop controlled LUT. In this paper a new Nonlinear Model Predictive Controller (NMPC) based on Particle Swarm Optimization (PSO) technique is proposed as a closed-loop approach for treating this disease. The proposed controller deals directly with the nonlinearity of the LUT, thus no need to use a linearized model or to represent it in a Piecewise Affine (PWA) framework. Besides, the proposed controller respects the given constraints over control signals and control signals variation. The obtained simulation results show the controller ability in controlling the micturition process and bringing the bladder behaviour to its normal function pattern. The proposed controller shows a good robustness against parameter variations. Meanwhile, the new developed technique is not considered as a computation burden, and on-line application is possible.

Paper Nr:	117
Title:	Multi-Objective Approach for Support Vector Machine Parameter Optimization and Variable Selection in Cardiovascular Predictive Modeling
Authors:	Christina Brester, Ivan Ryzhikov, Tomi-Pekka Tuomainen, Ari Voutilainen, Eugene Semenkin and Mikko Kolehmainen
Abstract:	We present a heuristic-based approach for Support Vector Machine (SVM) parameter optimization and variable selection using a real-valued cooperative Multi-Objective Evolutionary Algorithm (MOEA). Due to the possibility to optimize several criteria simultaneously, we aim to maximize the SVM performance as well as minimize the number of input variables. The second criterion is important especially if obtaining new observations for the training data is expensive. In the field of epidemiology, additional model inputs mean more clinical tests and higher costs. Moreover, variable selection should lead to performance improvement of the model used. Therefore, to train an accurate model predicting cardiovascular diseases, we decided to take a SVM model, optimize its meta and kernel function parameters on a true population cohort variable set. The proposed approach was tested on the Kuopio Ischemic Heart Disease database, which is one of the most extensively characterized epidemiological databases. In our experiment, we made predictions on incidents of cardiovascular diseases with the prediction horizon of 7–9 years and found that use of MOEA improved model performance from 66.8% to 70.5% and reduced the number of inputs from 81 to about 58, as compared to the SVM model with default parameter values on the full set of variables.
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Paper Nr:	121
Title:	Speed Estimation for Control of an Unmanned Ground Vehicle using Extremely Low Resolution Sensors
Authors:	Iván del Pino, Miguel Á. Muñoz-Bañón, Miguel Á. Contreras, Saúl Cova-Rocamora, Francisco A. Candelas and Fernando Torres
Abstract:	In mobile robotics, the low-level control is a key component that translates the desires of the high-level system into actual voltages and currents to drive the motors. PID controllers have been extensively used for speed control, but their performance depend heavily on the quality of the process variable (PV) estimation. In fact, noise and outliers --if not properly filtered-- might lead to system instability. In this work, we present a speed estimation strategy that enables us to develop an inexpensive, accurate and easy-to-install speed control solution. The proposed system relies on a Hall effect sensor and a Single-Dimensional Kalman Filter and its suitability is demonstrated through a number of real experiments controlling the speed of an Unmanned Ground Vehicle. We detail the design, implementation and validation processes and provide a GitHub repository with the developed software and CAD designs.
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Paper Nr:	126
Title:	Conical Tank Level Supervision using a Fractional Order Model Reference Adaptive Control Strategy
Authors:	Hanane Balaska, Samir Ladaci and Youcef Zennir
Abstract:	This paper proposes a fractional order model reference adaptive control (FO-MRAC) design in order to command the level of a conical tank system. The FO-MRAC is based on the choice of a fractional reference model which specifies the closed loop desired performances. Also, the control strategy adopted introduces fractional integration in the phase of corrector parameters updating. Model reference adaptive controller of integer order and of fractional order are applied to the non linear system and compared. From the simulation results, we concluded that FO-MRAC is the controller presenting the best performances, and especially in case of measurements noise, and parametric variations.
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Paper Nr:	135
Title:	Cluster-Based WSA for Decision Support Bayesian Systems: Case of Prognostic in Maintenance Management
Authors:	Imen Ben Brahim, Sid-Ali Addouche, Abderrahman El Mhamedi and Younes Boujelbene
Abstract:	A knowledge representation and reasoning from data have produced many models. Probabilistic graphical models, specifically the Bayesian Network (BN) have proved its worth. It is considered to be a very useful tool for representing uncertain knowledge and decision-making support. This presupposes availability of knowledge problem in the conditional probabilities form. However, one is often in a critical situation because of data are insufficient, partially unavailable or heterogeneous. Developing methods and techniques to reconstruct the corpus of data needed for decision making, especially via BN is called the ”knowledge elicitation”. Several elicitation methods exist but they are not always applicable, too demanding in expert knowledge or presenting limits. The most generic and useful is the Weighted Sum Algorithm (WSA) but it presents two major issues concerning the compatible parental configuration. In the present paper, we discuss what the literature proposes for the first one, then we develop the solution for the second and validate it via a case of pump failure prognostic tool based on Bayesian support decision.
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Paper Nr:	154
Title:	A Comparative Study on the Performance of MOPSO and MOCS as Auto-tuning Methods of PID Controllers for Robot Manipulators
Authors:	Ahmed Zidan, Svenja Tappe and Tobias Ortmaier
Abstract:	An auto-tuning method of PID controllers for robot manipulators using multi-objective optimization technique is proposed. Two approaches are introduced based on the multi-objective particle swarm optimization (MOPSO) and multi-objective cuckoo search (MOCS), respectively. The main goal of this work is to introduce a comparative study on the performance of both algorithms with respects to their applicability to the auto-tuning process. For this sake, necessary metrics are considered such as the hyperarea difference and the overall Pareto spread, among others. In order to generate a sufficient amount of statistical data, a simulation of the robot Puma 560 is implemented. Using a relatively accurate model of the robot dynamics, a PID controller is applied and an optimization problem is configured. Two objective functions are defined, namely the integral of absolute error and the variance of control action. In addition, two constraints are considered regarding the maximal position error and maximal motor torque. After defining the optimization problem, the two algorithms are implemented as auto-tuning methods of the controller gains. Execution of the tuning process is repeated 30 times to test the statistical power of the obtained results. After that, an experiment on a real robot is performed to gain an overview on the practical application of the proposed method. Finally, the performance of both algorithms are compared and conclusions about the efficiency of each one are made.
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Paper Nr:	156
Title:	Model Predictive Path Integral Control for Car Driving with Dynamic Cost Map
Authors:	Alexander Buyval, Aidar Gabdullin and Alexander Klimchik
Abstract:	Path planning in a complex dynamic environment is one of the key subsystems in an autonomous vehicle. This paper presents an extension of Model Predictive Path Integral (MPPI) control method which is able to take moving objects into account while path planning and driving. To obtain real-time performance, cost map update with respect to dynamic objects both as basic MPPI is implemented as a set of concurrent processes using CUDA technology. The algorithm’s performance is demonstrated on a model of a stock car in a simulation environment.
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Paper Nr:	159
Title:	Managing Weighted Preferences with Constraints in Interactive Applications
Authors:	Bandar Mohammed, Malek Mouhoub, Eisa Alanazi and Samira Sadaoui
Abstract:	Developing intelligent and interactive systems with visual user interfaces is essential for any website and mobile device. In this study, we propose a new web-based shopping system to elicit buyer’s requirements and preferences and to provide a set of suggestions accordingly. This process is achieved by first representing the elicited information through graphical models and then solving the underlying constrained problem. More precisely, we have used the Weighted CP-nets (WCP-net) graphical model to allow the user to express fine-grained preferences on the product attributes and their values in a quantitative or a conditional qualitative form. The latter has been extended in this paper to include constraints between attributes. A backtrack search algorithm is then performed to solve the constrained WCP-net and to return a set of Pareto optimal solutions satisfying all the constraints and maximizing all the preferences.
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Paper Nr:	165
Title:	A Novel Method for Grouping Variables in Cooperative Coevolution for Large-scale Global Optimization Problems
Authors:	Alexey Vakhnin and Evgenii Sopov
Abstract:	Large-scale global optimization (LSGO) is known as one of the most challenging problem for evolutionary algorithms (EA). In this study, we have proposed a novel method of grouping variables for the cooperative coevolution (CC) framework (random adaptive grouping (RAG))). We have implemented the proposed approach in a new evolutionary algorithm (DECC-RAG), which uses the Self-adaptive Differential Evolution (DE) with Neighborhood Search (SaNSDE) as the core search technique. The RAG method is based on the following idea: after some predefined number of fitness evaluations in cooperative coevolution, a half of subcomponents with the worst fitness values randomly mixes indices of variables, and the corresponding evolutionary algorithms reset adaptation of parameters. We have evaluated the performance of the DECC-RAG algorithm with the large-scale global optimization (LSGO) benchmark problems proposed within the IEEE CEC 2010. The results of numerical experiments are presented and discussed. The results have shown that the proposed algorithm outperforms some popular LSGO approaches.
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Paper Nr:	168
Title:	Comparison of Constraint-handling Techniques Used in Artificial Bee Colony Algorithm for Auto-Tuning of State Feedback Speed Controller for PMSM
Authors:	Rafal Szczepanski, Tomasz Tarczewski, Krystian Erwinski and Lech M. Grzesiak
Abstract:	This article focuses on comparison of two constraint-handling techniques: Deb’s Rules (DR) and Augmented Lagrangian (AL) applied to Artificial Bee Colony (ABC) algorithm that is used for auto-tuning of state feedback speed controller (SFC) for permanent magnet synchronous motor (PMSM). The task of the optimization algorithm is to determine the elements of Q and R weighting matrices in linear quadratic regulator (LQR) optimization process. Chosen matrices guarantee the best performance according to given optimization criteria. Safety and proper operation of the motor requires the use of constraint-handling (C-H) technique. The ABC in its original version cannot handle the constrained optimization problems, therefore necessary modifications of considered optimization algorithm are depicted. Simulation and experimental results showed that AL technique allows to obtain a better convergence of ABC algorithm and a better performance of the PMSM drive than DR technique.
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Paper Nr:	172
Title:	Linear Subset Size Scheduling for Many-objective Optimization using NSGA-II based on Pareto Partial Dominance
Authors:	Makoto Ohki
Abstract:	This paper describes techniques for improving the solution search performance of a multi-objective evolutionary algorithm (MOEA) in many-objective optimization problems (MaOP). As an MOEA for MaOP, we focus on NSGA-II based on Pareto partial dominance. NSGA-II based on Pareto partial dominance requires beforehand a combination list of the number of objective functions to be used for Pareto partial dominance. Moreover, the contents of the combination list greatly influence the optimization result. We propose to schedule a parameter r meaning the subset size of objective functions for Pareto partial dominance. This improvement not only releases users from the schedule of the parameter r but also improves the convergence to Pareto optimal solutions (POS) and the diversity of the individual set obtained by the optimization. Moreover, we propose to kill individuals of the archive set, where the individuals have the same contents as the individual created by the mating. This improvement excludes individuals with the same contents which obtained relatively good evaluations. The improved technique and other conventional techniques are applied to a many-objective 0/1 knapsack problem for verification of the effectiveness.
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Paper Nr:	182
Title:	Coevolutionary Algorithm for Multivariable Discrete Linear Time-variant System Identification
Authors:	Alexander E. Robles and Mateus Giesbrecht
Abstract:	A significant part of the works in system identification is focused on time-invariant dynamic systems. However, most of systems in the real applications have nonlinear and time variant behavior. In this paper, we present a multivariable time-variant identification method based on a paradigm in the field of evolutionary algorithms: The coevolutionary algorithm. This new method focuses on the relationship between the fitness of an individual in relation to the fitness of the other individuals (or group of individuals), based on the principle of the selective pressure, that is part of the evolutionary process. A brief comparison between a multivariable deterministic identification method MOESP-VAR and the proposed coevolutionary method is shown. From the results it is possible to notice that the proposed method presents an accuracy higher than the obtained with the deterministic identification method.
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Paper Nr:	210
Title:	Improvement of Water Resource Allocation Planning of Inland Waterways based on Predictive Optimization Approach
Authors:	Debora C. C. S. Alves, Eric Duviella and Arnaud Doniec
Abstract:	This paper presents a predictive optimization approach based on a quadratic minimization method to improve the water resource allocation planning of inland waterways. These networks are large scale systems composed of several interconnected reaches. Their management consists in keeping the water level of each reach close to an objective by allocating the available water resource among the network. It is particularly required in the context of global change where inland waterways should be strongly impacted by flood and drought events. The designed predictive optimization approach is achieved considering future horizons with the aim to reduce the impacts of extreme climate events thanks to anticipation of the management actions. A real part of the inland waterways in the north of France is considered in order to test the designed approach. The obtained management improvement comparing to water resource allocation planning methods that have been recently proposed in the literature is highlighted. The influence of the size of the predictive horizon is discussed.
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Paper Nr:	51
Title:	Scheduling Smart Loads in Modern Buildings based on Metaheuristic Optimization
Authors:	Mohammed Hijjo and Georg Frey
Abstract:	Load scheduling is one of the most promising trends in smart grids. It enables renewable energy to be efficiently utilized and accommodated in the smart buildings. In this work, we propose a comprehensive scheduling approach of a group of non-preemptive loads in a ‘greedy’ manner in order to reduce the deficit between the aggregate scheduled load and the available low-cost generation and therefore, the levelized cost of energy (LCoE) can be minimized. In order to reduce the massive searching space and attain a good schedule within a reasonable time, an efficient metaheuristic optimization framework is proposed and implemented based on genetic algorithms. An illustrative example is used to carry out this work using artificially created loads representing different facilities inside a building complex.
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Paper Nr:	60
Title:	In Vitro Test Bench with Intelligent Behavior to Ventricular Assist Devices
Authors:	Jeferson Cerqueira Dias, Jônatas Cerqueira Dias, Marcelo Barbosa, Diolino José Santos Filho, Fabrício Junqueira, Paulo Eigi Miyagi and Jose Roberto Cardoso
Abstract:	The abstract The Ventricular Assist Device (VAD) is a mechatronic device used to treat patients with heart failure who are able to use them in short- and long-term strategies. However, with increasing population longevity, long-term use has been intensified. Thus, the development of resources that improve the robustness and reliability of these devices is justified. This work proposes an in vitro test bench with intelligent behaviour that through a systematic of protocols for the collection, treatment and monitoring of reliability data, coming from standard curves of monitored variables, such as: flow, pressure, vibration, rotation, density, viscosity and temperature, provides a decision support system with user friendly interface for verification, validation and certification of VAD. The proposed method is descriptive of an in vitro test bed model for VAD that considers the use of Petri net for validation of the dynamic behaviour in front of the variables and a decision support system based on big data analytics technology with extraction of dada, which subsidizes intelligent behaviour. The proposed model is consistent with the bibliographic base and its validation. The Petri net allows confirming its application in the decision making, with intelligent behaviour, from the data mining.
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Paper Nr:	89
Title:	Evolutionnary Fixed-Structure LPV/LFT Controller Synthesis for Multiple Plants
Authors:	Philippe Feyel
Abstract:	This paper proposes to address the problem of fixed-structure gain-scheduled LPV/LFT controllers for plants with time-varying measurable and time invariant unmeasurable uncertainties. Due to the complexity of merging μ-technics with LPV/LFT approach, an alternative presented here consists in computing robust fixed-structure LPV/LFT controllers using the multiple plants framework instead of μ-technics. The complexity of this optimization problem is tackled with global evolutionary optimization. This paper shows that this approach is quite efficient and very simple to implement. The algorithm has been tested on the pendulum in the cart academic example.
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Paper Nr:	104
Title:	A Framework for Fault-tolerant Control for an Interacting and Non-interacting Level Control System using AI
Authors:	Himanshukumar R. Patel and Vipul A. Shah
Abstract:	In chemical and process industries, interacting and non-interacting level control systems are often used for material storage and processing. The level control parameter is very vital for dealing with faults in a system (leak), actuator or sensor. System and actuator faults occurring in a system may decrease the performance or cause instability and unsafe accidents. As observed from practice, when the control performance of the interacting and non-interacting systems decreases due to occurrence of faults, a fault-tolerant control strategy (FTC) is required. This paper presents a framework for passive fault tolerant control (PFTC) using a neural network (NN) and it is designed in order to ensure the stability robustness of the system in the presence of the faults. In fact, FTC is the potential strategy which is justified by its ability to preserve an acceptable performance in the presence of faults and process disturbances. To check the effectiveness of the proposed framework single-tank and two-tank level control experimental setup are used with system and sensor faults. Simulation and experiment results are presented to demonstrate the capability of the proposed framework of PFTC using NN to counteract the effect of the system, sensor and actuator faults.
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Paper Nr:	141
Title:	Safe PLC Controller Implementation IEC 61131-3 Compliant based on a Simple SAT Solver: Application to Manufacturing Systems
Authors:	Romain Pichard, Alexandre Philippot and Bernard Riera
Abstract:	In this study, manufacturing systems are considered as Discrete Event Systems (DES) with logical Inputs (sensors) and logical Outputs (actuators). In previous work, an original implementation of safe controllers (using safety logical constraints) for manufacturing systems, based on the use of a CSP (constraint satisfaction problem) solver, was proposed. However, the proposed solution was not IEC 61131-3 compliant. In other words, it was not possible to implement it in a PLC (Programmable Logic Controller). In this paper, a proof of concept IEC 61131-3 compliant has been carried out. To perform this challenge, an original simple CSP - SAT solver in ST (Structured Text) has been developed and programmed. The algorithm has been tested and validated by using a M340 Schneider Electric PLC and a box sorting simulated process using the FACTORY I/O software from the Real Games Company (www.realgames.co). It seems to be the first time that a SAT solver developed for PLC, is used in real time as a part of a PLC program to get a safe controller.
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Paper Nr:	173
Title:	Simultaneous Design of Structural and Control Systems using Set-based Design Method
Authors:	Haruo Ishikawa and Naoko Sasaki
Abstract:	The design method capable of considering the influence factors related to control and structural design systems under conditions that simultaneously satisfy multi-objective performances over both the systems is investigated. The influence factors and performances have some kinds of uncertainty related to structural design and control system design. The uncertainty may be expressed in terms of set interval. Set-based design method is available as a design method that can take account of such uncertainty. In the method, instead of optimization, the concept of satisficing is used. In the present study, the applicability of set-based design method that has been studied in the field of structural design is investigated for the simultaneously satisficing design of control and structural systems. For discussing the applicability, an example problem of inverted pendulum with heteromorphic shape on cart is solved by optimal regulator method in modern control theory. As a result, the set intervals of influence factors which simultaneously satisfy the set intervals of multi-objective performances are obtained. From this result, the usefulness of set-based design method for simultaneous design of control and structural systems can be confirmed.
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Paper Nr:	189
Title:	A Comparative Study of PID-PSO and Fuzzy Controller for Path Tracking Control of Autonomous Ground Vehicles
Authors:	Sami Allou and Youcef Zennir
Abstract:	The work presented in this paper focuses on platonning navigation control (train of vehicles) according to different trajectories. As a first step we based our study on two vehicles. an kinematic model of the two vehicles is described followed by a PID multi-controller control approach based on conventional PID, PID optimized by Particle Swarm Optimization (PSO) technique and fuzzy controller applied to the longitudinal and lateral control of each vehicle. Controller parameters optimization is based on a fitness function time weight square error (ITSE). The communication between the two vehicles is ensured with the exchange of information, the speed and orientation angle, respecting the safety distance between the vehicles. To approve our approach we have use different reference trajectory in different simulations in matlab-simulink environment and v-rep 3D simulation. The simulation obtained results illustrate the efficiency of our control design and open the perspectives for future work.
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Area 3 - Robotics and Automation

Full Papers

Paper Nr:	5
Title:	Facial Temperature Markers for Mental Stress Assessment in Human-Machine Interface (HMI) Control System
Authors:	Changjiang He, M. Mahfouf and L. A. Torres-Salomao
Abstract:	Mental state prediction is of great importance to human-machine interface (HMI) as far as both safety and reliability are concerned. In this paper, the use of facial temperature changes for predicting mental stress has been investigated. A carefully designed experiment of HMI has been performed on seven (7) healthy subjects, and the statistical analysis of the results has been provided, and the effectiveness of using facial temperature with the thermal camera to estimate the human mental stress has been established. The biomarkers developed from the data of facial temperature have exhibited a similar or even better ability to differentiate between the mental stress levels in comparison with the traditional biomarkers (e.g. heart rate variability (HRV), task load index (TLI) and pupil size). The mean nasal temperature has been shown to be sensitive to changes in the mental state, and the maximum facial temperature and the mean forehead temperature have also shown clear correlations with mental stress and task performance.
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Paper Nr:	9
Title:	Implementation, Identification and Control of an Efficient Electric Actuator for Humanoid Robots
Authors:	Florent Forget, Kevin Giraud-Esclasse, Rodolphe Gelin, Nicolas Mansard and Olivier Stasse
Abstract:	Autonomous robots such as legged robots and mobile manipulators imply new challenges in the design and the control of their actuators. In particular, it is desirable that the actuators are back-drivable, efficient (low friction) and compact. In this paper, we report the complete implementation of an advanced actuator based on screw, nut and cable. This actuator has been chosen for the humanoid robot Romeo. A similar model of the actuator has been used to control the humanoid robot Valkyrie. We expose the design of this actuator and present its Lagrangian model. The actuator being flexible, we propose a two-layer optimal control solver based on Differential Dynamical Programming. The actuator design, model identification and control is validated on a full actuator mounted in a work bench. The results show that this type of actuation is very suitable for legged robots and is a good candidate to replace strain wave gears.
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Paper Nr:	14
Title:	Singularity Loci and Kinematic Induced Constraints for an XY-Theta Platform Designed for High Precision Positioning
Authors:	Anas Hijazi, Jean-François Brethe and Dimitri Lefebvre
Abstract:	In this paper, the singularity analysis of an XY-Theta platform held by a serial redundant manipulator will be illustrated in details. This XY-Theta platform has a patented kinematics designed to keep the final position error below to 2 µm in its 300mm × 300mm workspace (Hijazi et al., 2015). These high performances are obtained due to the combination of three factors: proximity to a singular configuration allowed by a specific choice of the arm lengths to reduce the lever arm lengths, redundant kinematic chain to enlarge the dexterous workspace and a two-step control using mechanical breaks set up on the furthest joints and exteroceptive sensors in the final step. However, if the proximity of singularities is useful for the precision performance, it may also cause some control problems. Consequently, it is crucial to identify the singularity loci and the kinematic constraints they induce. This analysis is done in two cases: when the first joint is considered locked and the robot is not redundant anymore and when the robot can be controlled using the four joints. In the non-redundant case, the usual singularity surface degenerates into an helix. In the redundant case, singularity surfaces may appear in specific configurations. In both cases, the induced kinematic constraints are analyzed and strategies are proposed to overcome the problems.
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Paper Nr:	17
Title:	Improved Cloud Partitioning Sampling for Iterative Closest Point: Qualitative and Quantitative Comparison Study
Authors:	Polycarpo Souza Neto, Nicolas S. Pereira and George A. P. Thé
Abstract:	In 3D reconstruction applications, an important issue is the matching of point clouds corresponding to different perspectives of a given object in a scene. Traditionally, this problem is solved by the use of the Iterative Closest point (ICP) algorithm. In view of improving the efficiency of this technique, authors recently proposed a preprocessing step which works prior to the ICP algorithm and leads to faster matching. In this work, we provide some improvements in our technique and compare it with other 4 variations of sampling methods using a RMSE metric, an Euler angles analysis and a modification structural similarity (SSIM) based metric. Our experiments have been carried out on four different models from two different databases, and revealed that our cloud partitioning approach achieved more accurate cloud matching, in shorter time than the other techniques. Finally we tested the robustness of the technique adding noise and occlusion, obtaining, as in the other tests, superior performance.
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Paper Nr:	22
Title:	Shared Admittance Control for Human-Robot Co-manipulation based on Operator Intention Estimation
Authors:	Jonathan Cacace, Alberto Finzi and Vincenzo Lippiello
Abstract:	Collaborative robots are increasingly employed in industrial workplaces, assisting human operators in decreasing the weight and the repetitiveness of their activities. In this paper, we assume the presence of an operator cooperating with a lightweight robotic arm, able to autonomously navigate its workspace, while the human co-worker physically interacts with it leading and influencing the execution of the shared task. In this scenario, we propose a human-robot co-manipulation method in which the autonomy of the robot is regulated according to the operator intentions. Specifically, the operator contact forces are assessed with respect to the autonomous motion of the robot inferring how the human motion commands diverges from the autonomous ones. This information is exploited by the system to adjust its role in the shared task, leading or following the operator and to proactively assist him during the co-manipulation. The proposed approach has been demonstrated in an industrial use case consisting of a human operator that interacts with a Kuka LBR iiwa arm to perform a cooperative manipulation task. The collected results demonstrate the effectiveness of the proposed approach.
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Paper Nr:	27
Title:	Nonlinear Design of Model Predictive Control Adapted for Industrial Articulated Robots
Authors:	Květoslav Belda
Abstract:	This paper introduces a specific nonlinear design of the discrete model predictive control based on the features of linear methods used for the numerical solution of ordinary differential equations. The design is intended for motion control of robotic or mechatronic systems that are usually described by nonlinear differential equations up to the second order. For the control design, the explicit linear multi-step methods are considered. The proposed way enables the design to apply nonlinear model to the construction of equations of predictions used in predictive control. An example of behavior of proposed versus linear predictive control is demonstrated by a comparative simulation with nonlinear mathematical model of six-axis articulated robot.
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Paper Nr:	44
Title:	Active Haptic Control for a Biologically Inspired Gripper in Reconfigurable Assembly Systems - Testing Active Haptic Control through Force Feedback
Authors:	Christian Ivan Basson and Glen Bright
Abstract:	Haptic feedback for flexible grippers enhances control over human-machine interaction and object manipulation. Force feedback control through a haptic sensory system enables gripping sensitivity for the grasping of fragile components. The development of intelligent gripping systems has the potential to be implemented in Reconfigurable Assembly Systems, (RAS), for on-demand production lines. Advancements in object control and successful object handling for assembling systems were investigated. An active haptic control system was developed to assess the adaptability of gripper appendage grip force through a dynamic pick and place movement. The aim was to determine the force output from a self-adjusting grasping procedure using a haptic feedback control sensory system. The force output data was empirically collected and plotted on a signal verse time graph. The voltage signal representing the actual grasp force throughout a gripping procedure. The testing was performed on a previously manufactured gripper based on a biologically inspired phenomenon called the Fin Ray Effect®. Conclusions and recommendations were made in relation to effective grip force control.
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Paper Nr:	50
Title:	Quantitative Assessment of Robotic Swarm Coverage
Authors:	Brendon G. Anderson, Eva Loeser, Marissa Gee, Fei Ren, Swagata Biswas, Olga Turanova, Matt Haberland and Andrea L. Bertozzi
Abstract:	This paper studies a generally applicable, sensitive, and intuitive error metric for the assessment of robotic swarm density controller performance. Inspired by vortex blob numerical methods, it overcomes the shortcomings of a common strategy based on discretization, and unifies other continuous notions of coverage. We present two benchmarks against which to compare the error metric value of a given swarm configuration: nontrivial bounds on the error metric, and the probability density function of the error metric when robot positions are sampled at random from the target swarm distribution. We give rigorous results that this probability density function of the error metric obeys a central limit theorem, allowing for more efficient numerical approximation. For both of these benchmarks, we present supporting theory, computation methodology, examples, and MATLAB implementation code.
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Paper Nr:	54
Title:	Development of the Sensory Network for the Vibration-based Fault Detection and Isolation in the Multirotor UAV Propulsion System
Authors:	Adam Bondyra, Przemysław Gąsior, Stanisław Gardecki and Andrzej Kasiński
Abstract:	In this paper, a fault detection and isolation (FDI) system for propeller impairments of the multirotor UAV is presented. The algorithm is based on the processing of signal vectors from the set of vibration sensors located close to the propulsion units. Axial and radial vibrations are measured using MEMS accelerometers that provide data for the feature extraction based on the Fast Fourier Transform (FFT). Characteristic fault signatures extracted from vibration signals are used to detect and localize damaged blades using the set of random decision trees. A method was evaluated with data gathered during numerous test flights and validated in relation to signal acquisition time and number of classifiers in the ensemble. Results show over 95% sensitivity in detecting and isolating faulty rotor states. The presented approach is an effective and low-cost solution, very versatile to implement in the arbitrary UAV.
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Paper Nr:	59
Title:	Flexible Motion Planning for Object Manipulation in Cluttered Scenes
Authors:	Marco Costanzo, Giuseppe De Maria, Gaetano Lettera, Ciro Natale and Salvatore Pirozzi
Abstract:	The work implements a new real-time flexible motion planning method used for reactive object manipulation in pick and place tasks typical of in-store logistics scenarios such as shelf replenishment of retail stores. This method uses a new hybrid pipeline to recognize and localize an object observed through a depth camera, by integrating and optimizing state of the art techniques. The proposed algorithm guarantees recognition robustness and localization accuracy. The desired object is then manipulated. The motion planner, based on the obstacles detected in the scene, plans a collision-free path towards the target pose. The planned trajectory optimizes a cost function that reflects the best solution among those available and produces natural and smooth path through a smart IK constrained solution which avoids robot unnecessary reconfigurations. A reactive control based on distributed proximity sensors is finally adopted to locally modify the planned trajectory in real time to avoid collisions with uncertain or dynamic obstacles. Experimental results in a supermarket scenario populated with cluttered obstacles demonstrate smoothness of the robot motions and reactive capabilities in a typical fetch and carry task.
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Paper Nr:	73
Title:	Dynamical Investigation of Crawling Motion System based on a Multistable Tensegrity Structure
Authors:	Philipp Schorr, Valter Böhm, Lena Zentner and Klaus Zimmermann
Abstract:	The basic idea of this article is the utilization of the multistable character of a compliant tensegrity structure to control the direction of motion of a crawling motion system. A crawling motion system basing on a two-dimensional tensegrity structure with multiple stable equilibrium states is considered. This system is in contact with a horizontal plane due to gravity. For a selected harmonic actuation of the system small oscillations around the given equilibrium state of the tensegrity structure occur and the corresponding uniaxial motion of the system is evaluated. A change of the equilibrium state of the tensegrity structure yields to novel configuration of the entire system. Moreover, the motion behavior of the novel configuration is totally different although the actuation strategy is not varied. In particular, the direction of motion changes. Therefore, this approach enables a uniaxial bidirectional crawling motion with a controllable direction of motion using only one actuator with a selected excitation frequency.
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Paper Nr:	82
Title:	A Spatial Motion Control to Transfer an Object between a Pair of Air Jet
Authors:	Kazuki Yoshinaga, Satoshi Iwaki, Naoki Tsuchihashi, Nobukado Abe, Tetsushi Ikeda, Toshiharu Kosaku and Takeshi Takaki
Abstract:	We propose a method in which multiple nozzles are arranged consecutively along a conveying line and an object can be relayed one after another. In this paper, as a most essential technology for such a conveyor, we focus on the transferring control of the object between a pair of air jet on a vertical plane. We propose a relaying control method based on some natural behaviours of an object in a fluid field where two air jet streams collide. Some successful experiment results are shown.
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Paper Nr:	88
Title:	A Brake-based Assistive Wheelchair Considering a Seat Inclination
Authors:	Daisuke Chugo, Ryo Kohara, Masahiro Iwaki, Satoshi Muramatsu, Sho Yokota and Hiroshi Mashimoto
Abstract:	Considering the road inclination conditions, we proposed an upper body posture adjustment system for a passive-type assistive wheelchair. On an inclined road, there is a high probability that a wheelchair will move in a direction that is different from that desired by its user. In our previous research, we proposed a system that estimated a wheelchair user’s intentions and worked passively to complement their intentional force. This was accomplished by negating the wheel traction that was generated by the road’s inclination using only the servo brakes on each wheel. However, in some cases, our system failed to assist the driving motion of the user because it negated only the gravitational force. Therefore, our wheelchair succeeded in avoiding the unintended movement, but its user was required to row the hand rims with a considerable amount of force to overcome these braking forces. Consequently, we proposed an upper body posture adjustment system that adapts to the inclined road conditions and reduces the wheel traction that is generated by gravity. The proposed system inclined the wheelchair seat and aligned the upper body posture of its user to the center position of the wheelchair. Using this method, the proposed system maintained the position of the user’s center of gravity with respect to the center position of the wheelchair. Our experimental findings suggested that the proposed passive-type assistive wheelchair can complement the user’s intentional force with smaller brake traction, indicating that the user can drive the wheelchair using less physical strength.
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Paper Nr:	97
Title:	Internal Simulation for Autonomous Robot Exploration of Lava Tubes
Authors:	Raúl Domínguez, Sascha Arnold, Christoph Hertzberg and Arne Böckmann
Abstract:	Space Exploration stands as one of the most challenging endeavors of our time. Extraterrestrial caves in particular have been identified by the scientific community as of great interest. They could be suitable for allocating astronaut planetary stations, but little is known about them. In this paper, we describe and analyze robotic cave exploration using internal simulation and SLAM technologies and provide experimental results. The experiments were performed in a lava tube selected due to its representativeness as space analog. Expensive mission costs, communication constraints and navigational challenges in space missions demand highly developed degrees of autonomy and safety on the robots. For this reason, our solution incorporates methods for the validation of paths based on on-board, internal simulation. The methods provide the means to increase the confidence of successful executions by simulating using physics models the planned path. A highly realistic model of the robot and an on-line generated model of the environment are required. Assuming the demands of the space robotics scenario, all software runs on-board.
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Paper Nr:	100
Title:	Knee Rehabilitation Device with Soft Actuation: An Approach to the Motion Control
Authors:	Leonardo Solaque, Marianne Romero and Alexandra Velasco
Abstract:	Assistive devices in rehabilitation have gained much attention in robotics research. Recent actuation systems include compliant elements to provide advantages as natural motions and safety in the interaction with humans. These are the so-called soft actuators, among which there are series elastic actuators (SEA) and variable stiffness actuators (VSA). On the other hand, control strategies are required in order to accomplish desired tasks in a proper manner. In rehabilitation systems this is to reproduce a desired motion without affecting the patient, so the control system is crucial. In this paper, we present a control strategy for a knee rehabilitation device, with soft actuation. The goal is to control the system while maintaining the intrinsic softness of the system when the patient is in the rehabilitation process. We propose a feedback control strategy, acting in a defined threshold to maintain the stiffness of the system, combined with a feedforward decision control to reject disturbances.
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Paper Nr:	115
Title:	Path Tracking of a Bi-steerable Mobile Robot: An Adaptive Off-road Multi-control Law Strategy
Authors:	Roland Lenain, Ange Nizard, Mathieu Deremetz, Benoit Thuilot, Vianney Papot and Christophe Cariou
Abstract:	This paper proposes a path tracking control algorithm dedicated to off-road mobile robots equipped with two steering axles. Four wheel steering mobile robot allows to enhanced motion capability with respect to classical car-like mobile robot, while reducing the friction induced by the skid-steered architecture. In particular, such a kinematic structure makes it possible to independently control the robot heading and its position, or to increase turning capabilities. In this paper, a strategy is developed in order to reduce the space required when achieving manoeuvres around a desired trajectory. Contrarily to classical point of view, expressing a relationship between the front and rear wheels, the control laws here proposed aim at following the same path for the front and the rear centre of the axle. The robot is then split into two subsystems, regulating two lateral deviations with respect to a desired trajectory.
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Paper Nr:	116
Title:	Improved Discrete RRT for Coordinated Multi-robot Planning
Authors:	Jakub Hvězda, Miroslav Kulich and Libor Přeučil
Abstract:	This paper addresses the problem of coordination of a fleet of mobile robots – the problem of finding an optimal set of collision-free trajectories for individual robots in the fleet. Many approaches have been introduced during last decades, but a minority of them is practically applicable, i.e. fast, producing near-optimal solutions, and complete. We propose a novel probabilistic approach based on the Rapidly Exploring Random Tree algorithm (RRT) by significantly improving its multi-robot variant for discrete environments. The presented experimental results show that the proposed approach is fast enough to solve problems with tens of robots in seconds. Although the solutions generated by the approach are slightly worse than one of the best state-of-the-art algorithms presented in (ter Mors et al., 2010), it solves problems where ter Mors’s algorithm fails.
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Paper Nr:	174
Title:	Compliance Error Compensation based on Reduced Model for Industrial Robots
Authors:	Shamil Mamedov, Dmitry Popov, Stanislav Mikhel and Alexandr Klimchik
Abstract:	In the near future industrial manipulators can completely replace bulky and expensive CNC machines. The only issue that stands in a way of this transition is low stiffness of industrial robots. However, a lot of research is going on in this area with the focus on developing an accurate stiffness model of the robot and embedding it into the control scheme. The majority of the stiffness models include stiffness of the links as well as joints even though typically complete link parameters are not provided by the robot manufacturers. Therefore, it is of great importance to understand how accurately a reduced stiffness model which takes into account only joint stiffness can replicate the results of the full model. In this paper, we focus on analyzing the quantitative difference between these two models using Virtual Joint Modeling method and its effect on trajectory tracking. The systematic analysis demonstrates that reduced stiffness model can quite accurately replicate the full one and with reduced model, up to 95 percent of the end-effector deflection can be compensated so that the average deflection error after compensation is about 0.8 ߤ݉ tor a typical heavy industrial robot under the loading.
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Paper Nr:	184
Title:	Force Control of Surgical Robot with Time Delay using Model Predictive Control
Authors:	Jasmeet Singh Ladoiye, Dan S. Necsulescu and Jurek Sasiadek
Abstract:	Tele-surgical robotic systems are making our vision of “virtual open surgery” into reality by using minimum invasive techniques with laparoscopic vision technology. The commercial available minimally invasive robotic systems (MIRS) force the surgeons to forgo the ability to touch and feel the environment, unlike conventional open surgery. Surgeons rely on the visual feedback from the patient’s side at the master console to get information about the operation site. The control gets even more difficult in the teleoperated surgical systems due to random network delays. The difference in the network delay in data and perception makes hand to eye coordination even more difficult. Force feedback can offer surgeon instant perception of the physical properties at the operating end. A novel approach is proposed to control the force of a surgical robot suffering from signal delays using model predictive control. The proposed MPC-scheme of force control in between the master and slave station shows compensation of the deterministic time delays.
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Paper Nr:	199
Title:	Energy Efficient Path Planning of Hybrid Fly-Drive Robot (HyFDR) using A* Algorithm
Authors:	Amir Sharif, H. M. Lahiru, S. Herath and Hubert Roth
Abstract:	Hovering flight is agile and energy expansive, but driving on ground is slow and energy efficient method of locomotion. To get the benefits of these two methods of locomotion, we combined them in a single platform named as HyFDR. It is a Quadcopter with powered wheels, it can fly in air and drive on ground. Autonomous navigation of HyFDR creates new challenges in the field of path planning. The goal is to simulate the navigation of HyFDR with minimum energy consumption using A* algorithm. Depending upon the terrain, obstacles, energy constraints, and desired flight time, HyFDR can autonomously switch between flight mode, drive mode and hybrid mode. We showed that in some cases HyFDR is energy efficient than Quadcopter.
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Paper Nr:	204
Title:	Constant Curvature Kinematic Model Analysis and Experimental Validation for Tendon Driven Continuum Manipulators
Authors:	S. Mosqueda, Y. Moncada, C. Murrugarra and H. León-Rodriguez
Abstract:	In this paper an analysis is done to the current kinematic model for continuum robot, with the goal of determining the accuracy of the experimental validation of the constant curvature kinematic model to establish a relation between the mathematical model and continuum robot, and its feasibility of applying for any type of continuum structure, measuring the end effector planar trajectory based on the displacement of passive cables located along the structure. To test the kinematic model, a prototype of continuous robot composed of 1 segment with 7 sections, controlled by 3 cables, per section was fabricated, we also propose a modular segment (link) with free joints, the modularity allows to extend the length of the segment and also allows to add segments and connect in the form of serial chain and describe the radius of concave and/or convex curvature and allow the robot manipulator to follow different trajectories and displacements in their workspace. The kinematic model of constant curvature used in continuous robots with minimal positioning errors was implemented and tested.
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Paper Nr:	217
Title:	An Inverse Perspective Mapping Approach using Monocular Camera of Pepper Humanoid Robot to Determine the Position of Other Moving Robot in Plane
Authors:	M. Hassan Tanveer and Antonio Sgorbissa
Abstract:	This article presents a method to know the position of object or moving robot in the plane while the camera is moving dynamically. An Inverse Perspective mapping (IPM) approach has been embedded in a monocular camera on Head of Pepper Humanoid Robot (Softbank Robotics) for real time position determination of other object or robot in plane. While the Pepper head is moving, it is difficult to determine position or distance to objects in front of the robot with any different degree of certainity. By applying IPM, a linear relationship between the IPM frame and world frame becomes the key element to know the position of object while the head is static but when the head orientation changes the IPM is modified to adapt the linear relationship between both frames. So, the proposed method is based on the extraction of accurate bird’s-eye view. The method includes the Image Acquistion, IPM Filtering, Detection Phase, Region of Interest Selection and Pixel remapping.
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Short Papers

Paper Nr:	12
Title:	Efficient Fuzzy based Image Mosaicing Algorithm for Overlapped Aerial Images
Authors:	Abdelhai Lati, Mahmoud Belhocine and Noura Achour
Abstract:	This article presents an efficient technique for aerial image mosaicing algorithm of overlapped pair of Unmanned Aerial Vehicle (UAV) images. Our algorithm is based on detecting some sparse distinguished set of pixels from captured image. Therefore, in the first stage, FAST algorithm was proposed for determining locations of feature pixels. Local binary pattern (LBP) technique is robust for describing features pixels, but it still suffers from different problems, such as noise and errors in interpolating values of surrounding pixels. Fuzzy logic theory partially solves the noise sensitivity problem associated with LBP approach, therefore; in the second part of this article, a robust method based on fuzzy logic technique was used to create Fuzzy Improved Local Binary Patterns descriptors (Fuzzy ILBPDs) for features matching purpose, after that; homography matrix will be estimated through the best associated features; in order to project the overlapped UAV images. The results of our algorithm maps for some benchmark and effective numerical comparisons with previous related works are presented in this paper.
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Paper Nr:	18
Title:	CILAP-Architecture for Simultaneous Position- and Force-Control in Constrained Manufacturing Tasks
Authors:	Sophie Klecker, Bassem Hichri and Peter Plapper
Abstract:	This paper presents a parallel control concept for automated constrained manufacturing tasks, i.e. for simultaneous position- and force-control of industrial robotic manipulators. The manipulator’s interaction with its environment results in a constrained non-linear switched system. In combination with internal and external uncertainties and in the presence of friction, the stable system performance is impaired. The aim is to mimic a human worker’s behaviour encoded as lists of successive desired positions and forces obtained from the records of a human performing the considered task operating the lightweight robot arm in gravity compensation mode. The suggested parallel control concept combines a model-free position- and a model-free torque-controller. These separate controllers combine conventional PID- and PI-control with adaptive neuro-inspired algorithms. The latter use concepts of a reward-like incentive, a learning system and an actuator-inhibitor-interplay. The elements Conventional controller, Incentive, Learning system and Actuator-Preventer interaction form the CILAP-concept. The main contribution of this work is a biologically inspired parallel control architecture for simultaneous position- and force-control of continuous in contrast to discrete manufacturing tasks without having recourse to visual inputs. The proposed control-method is validated on a surface finishing process-simulation. It is shown that it outperforms a conventional combination of PID- and PI-controllers.
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Paper Nr:	38
Title:	Evaluating the Robustness of Global Appearance Descriptors in a Visual Localization Task, under Changing Lighting Conditions
Authors:	Vicente Román, Luis Payá and Óscar Reinoso
Abstract:	Map building and localization are two important abilities that autonomous mobile robots must develop. This way, much research has been carried out on these topics, and researchers have proposed many approaches to address these problems. This work presents some possibilities to solve these problems robustly using global appearance descriptors. In this way, robots capture visual information from the environment and obtain, usually by means of a transformation, a global appearance description for each whole image. Using these descriptors, the robot is able to estimate its position in a previously built map, which is also composed of a set of global appearance descriptors. In this work, the global appearance descriptors performance at the localization task inside a known environment has been studied. In the assignment a map is already built and the goal is to evaluate the descriptors’ robustness to perform localization tasks when the environment visual appearance changes substantially. To achieve this objective, a comparative evaluation of several global appearance descriptors is carried out.
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Paper Nr:	56
Title:	Registration of Inconsistent Point Cloud Maps with Large Scale Persistent Features
Authors:	Simon Thompson, Masahi Yokozuka and Naohisa Hashimoto
Abstract:	Accurate point cloud registration techniques such as Iterative Closest Point matching have been developed to produce large scale 3D maps of the environment. Typically they iteratively register point clouds captured from adjacent sensor scans resulting in point clouds which are largely consistent. However, merging two seperate point cloud maps constructed at different times can lead to significant inconsistencies between the point clouds. Existing point based registration techniques can be sensitive to local minima caused by such inconsistencies. Feature based approaches can overcome local minimum but are typically less accurate, and can still suffer from correspondence errors. We introduce Large Scale Persistent Features (LSPFs), sub regions of point clouds that have orthogonal planar regions that are consistent and persist over a large spatial area. Each LSPF is used to calculate an individual transformation estimate using traditional registration techniques. Sampling Consensus is then used to select the best transform which is used for registration, avoiding local minima. LSPF registration is applied to simulated point cloud maps with known inconsistencies and shown to perform with more accuracy and lower computation time than other popular approaches. In addition, real world registration results are presented which demonstrate LSPF registration between MMS maps and low cost sensor maps captured 6 months apart.
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Paper Nr:	61
Title:	A Training Simulator for Teleoperated Robots Deployed at CERN
Authors:	Clare Saliba, Marvin K. Bugeja, Simon G. Fabri, Mario Di Castro, Alessandro Mosca and Manuel Ferre
Abstract:	This paper presents the design and implementation of a training simulator for the teleoperated robot Telemax. Telemax is used at CERN for inspection and maintenance operations to reduce the exposure of personnel to radiation. The robot is modelled using a robot description format and spawned in the robotic simulator Gazebo. Control schemes are implemented in ROS in order to actuate the robotic arm in both joint-by-joint space and operational-space. Control of the robot base is also modelled. A graphical user interface is used in order to interface with the simulation, and control the robot with the help of live images coming from the robot’s on-board cameras. The resulting simulator was tested by robot operators at CERN and is envisaged to be of great help in the training of new operators, as well as in the testing of robot interventions in new scenarios and environments.
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Paper Nr:	81
Title:	LightByte: Communicating Wirelessly with an Underwater Robot using Light
Authors:	Robert Codd-Downey and Michael Jenkin
Abstract:	Communication with and control of underwater autonomous vehicles is complicated by the nature of the water medium which absorbs radio waves over short distances and which introduces severe limitations on the bandwidth of sound-based technologies. Given the limitations of acoustic and radio frequency (RF) communication underwater, light-based communication has also been used. Light-based communication is also emerging as an effective strategy for terrestrial communication. Can the emerging Light Fidelity (Li-Fi) communication standard be exploited underwater to enable devices in close proximity to communicate by light? This paper describes the development of the LightByte Li-Fi model for underwater use and experimental evaluation of its performance both terrestrially and underwater.
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Paper Nr:	86
Title:	Pitching and Catching of an Object between a Pair of Air Jet
Authors:	Nobukado Abe, Satoshi Iwaki, Kazuki Yoshinaga, Naoki Tsuchihashi, Tetsushi Ikeda, Toshiharu Kosaku and Takeshi Takaki
Abstract:	We have been studying an air jet manipulation technology to non-contactly carry an object over a long distance using multiple 3D air jet manipulation modules consisting of a single air jet nozzle and a pan-tilt actuator. Here we challenge long distant transportation through object pitching-and-catching between a pair of air jet. In this report, we propose a control algorithm to determine each air jet angle and its flow rate, for both pitching side and catching side. First we try to observe human behaviour in a real catch-ball as a hint to create the algorithm. Next, as a preliminary experiment, a pitching experiment and a catching experiment are independently performed to obtain an air jet output function and a control law for each. After that, we propose an integrated transporting algorithm of pitching and catching, and confirm its validity by demonstration experiment.
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Paper Nr:	90
Title:	3D Pose Estimation of Bin Picking Object using Deep Learning and 3D Matching
Authors:	Junesuk Lee, Sangseung Kang and Soon-Yong Park
Abstract:	In this paper, we propose a method to estimate 3D pose information of an object in a randomly piled-up environment by using image data obtained from an RGB-D camera. The proposed method consists of two modules: object detection by deep learning, and pose estimation by Iterative Closest Point (ICP) algorithm. In the first module, we propose an image encoding method to generate three channel images by integrating depth and infrared images captured by the camera. We use these encoded images as both the input data and training data set in a deep learning-based object detection step. Also, we propose a depth-based filtering method to improve the precision of object detection and to reduce the number of false positives by preprocessing input data. ICP-based 3D pose estimation is done in the second module, where we applied a plane-fitting method to increase the accuracy of the estimated pose.
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Paper Nr:	91
Title:	A Framework for the Segmentation and Classification of 3D Point Clouds using Temporal, Spatial and Semantic Information
Authors:	Mehmet Ali Çagri Tuncer and Dirk Schulz
Abstract:	This paper proposes a novel framework for the segmentation and classification of 3D point cloud which jointly uses spatial, temporal and semantic information. It improves the classification performance by reducing under-segmentation errors. The presented framework, which can determine the number and label of objects in each spatially extracted blob, is decomposed into three steps to acquire spatial, temporal and semantic cues. For the spatial features, blobs are extracted spatially with a neighborhood system on an occupancy grid representation. A smoothed motion field is estimated for the acquisition of temporal cue, where the grid cells are tracked using individual Kalman filters and estimated velocities are transformed to one dimensional movement directions. A support vector machine (SVM) classifier is trained to discriminate the classes of interest for the semantic information of the blobs. A confidence metric is defined to probabilistically compare the volume of each classified blob with the volume of an average object for that class. If this metric is below a predefined threshold, a sequential variant of distance dependent Chinese restaurant process (s-ddCRP) performs the final partition in this blob by using spatial and temporal information. If the s-ddCRP approach splits the blob, the partitioned sub-blobs are afterwards reassigned to new objects by the classifier. Otherwise, the queried blob remains the same. This procedure iteratively continues while searching each blob in the scene at each time frame. Experiments on data obtained with a Velodyne HDL64 scanner in real traffic scenarios illustrate that the proposed framework improves the classification performance of an SVM classifier by reducing under-segmentation errors.
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Paper Nr:	99
Title:	Approximating Viability Kernels of Non-linear Systems
Authors:	André M. Carvalho and João S. Sequeira
Abstract:	A typical concern in Robotics is to assess if it is possible to keep a robot inside a set of safe states, e.g., an autonomous car that must stay on the road. That is closely tied with the problem of computing the viability kernel of the system, i.e., the largest set of initial states for which it is guaranteed that the system has controls that keep maintain the trajectories inside the constraint set. The approach in this paper builds on previous work, on linear sampled-data systems. It is based on sampling the boundary of the constraint set, finding the states inside the viability kernel using finite-horizon forward simulation. Our adaptation extends the original algorithm, approximating the viability kernel for some non-linear systems through linearization methods. The non-linear systems here approached are the ones described by first order differential equations with continuous derivatives and convex with respect to the inputs. Existence and uniqueness conditions are also established to ensure adequate results for the whole algorithm. A practical example, with a simple non-linear system, to illustrate the proposed algorithm is also presented.
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Paper Nr:	109
Title:	Influence of Human Limb Motion Speed in a Collaborative Hand-over Task
Authors:	Matteo Melchiorre, Leonardo Sabatino Scimmi, Stefano Mauro and Stefano Pastorelli
Abstract:	The paper analyses a possible cooperative task between a human operator and a robot. Operator and robot are interfaced by Microsoft Kinect® which is used to detect the position of an upper limb of the operator. The robot is driven by a control algorithm designed to track the hand of the human and to obtain a hand-over in the final part of the trajectory. The paper describes the algorithm and shows its performance with different velocities of the limbs by means of tests carried out in a simulation environment.
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Paper Nr:	112
Title:	Sliding Mode Control in Mobile Platform Joint Space for Multi-body Cable Driven Robot
Authors:	Hachmia Faqihi, Maarouf Saad, Khalid Benjelloun, Mohammed Benbrahim and M. Nabil Kabbaj
Abstract:	The aim of this paper is to develop a suitable control of Multi-Body Cable-Driven Robot with satisfactory tensionnability condition. The desired trajectory is given in joint mobile platform space and thereby transformed on joint actuator space using the developed inverse kinematic. Under the control scheme, the actuator joint coordinates obtained by the sensor are used as feedback for the control system. Adding to the error in joint actuator space, the cable tensions which are computed based on the mobile platform dynamic and the optimization problem are used as inputs of the controller. The sliding mode control method based on linear reaching law is used to control the effector of the robot. Asymptotic stability of the closed loop system is analyzed through Lyapunov theorem. Finally, a motion tracking based on the proposed control strategy is carried out on the Multi Body Cable-Driven Robot. The obtained results show the effectiveness and the feasiblity of the proposed control method.
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Paper Nr:	129
Title:	Learning-based Kinematic Calibration using Adjoint Error Model
Authors:	Nadia Schillreff and Frank Ortmeier
Abstract:	A learning-based robot kinematic calibration approach based on the product-of-exponentials (POE) formula and Adjoint error model is introduced. To ensure high accuracy this approach combines the geometrical and non-geometrical influences like for e.g. elastic deformations without explicitly defining all physical processes that contribute to them using a polynomial regression method. By using the POE formula for kinematic modeling of the manipulator it is ensured that kinematic parameters vary smoothly and used method is robust and singularity-free. The introduced error parameters are presented in the form of Adjoint transformations on nominal joint twists. The calibration process then becomes finding a set of polynomial functions using regression methods that are able to reflect the actual kinematics of the robot. The proposed method is evaluated on a dataset obtained using a 7-DOF manipulator (KUKA LBR iiwa 7 R800). The experimental results show that this approach significantly reduces positional errors of the robotic manipulator after calibration.
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Paper Nr:	134
Title:	Automation of Intralogistic Processes through Flexibilisation - A Method for the Flexible Configuration and Evaluation of Systems of Systems
Authors:	Marco Bonini, Augusto Urru, Sebastian Steinau, Selcuk Ceylan, Matthias Lutz, Jan Schuhmacher, Kevin Andrews, Harry Halfar, Stefan Kunaschk, Asadul Haque, Vinu Nair, Matthias Rollenhagen, Nayabrasul Shaik, Manfred Reichert, Norbert Bartneck, Christian Schlegel, Vera Hummel and Wolfgang Echelmeyer
Abstract:	The high system flexibility necessary for the full automation of complex and unstructured tasks leads to increased technological complexity, thus to higher costs and lower performance. In this paper, after an introduction to the different dimensions of flexibility, a method for flexible modular configuration and evaluation of systems of systems is introduced. The method starts from process requirements and, considering factors such as feasibility, development costs, market potential and effective impact on the current processes, enables the evaluation of a flexible systems of systems equipped with the needed functionalities before its actual development. This allows setting the focus on those aspects of flexibility that add market value to the system, thus promoting the efficient development of systems addressed to interested customers in intralogistics. An example of application of the method is given and discussed.
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Paper Nr:	136
Title:	Data Management System for Drive-based Smart Data Services - A Pratical Approach for Machine-Internal Monitoring Applications
Authors:	Chris Schoeberlein, André Sewohl, Holger Schlegel and Matthias Putz
Abstract:	In the field of machine tools, a continuous trend towards automated and networked production systems is recognizable in order to cope with the autonomous and self-organized systems promoted within Industry 4.0. For this purpose, large quantities of partially unstructured data exist within the machine-internal control system. The informational value of this data can be enhanced by suitable algorithms and utilized for multivalent applications. In addition to the information of the computerized numerical control such as feed rate or axis positions the drive systems of machine tools can be consulted. The major advantage of the drive internal information is due to the high temporal resolution of the available data, which is significantly above the interpolation cycle of modern CNC (e.g. Siemens 840D sl). However, a major obstacle is the access to this information, since most of the parameters are processed directly in the drive internal control loops and therefore not transmitted to the superordinate control. Within the paper, a practical solution for the automatic acquisition and processing of drive data is presented. Based on a machine internal data management system in combination with an industrial embedded system the extraction and aggregation of control loop data in the sense of so-called Smart Data Services is realized.
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Paper Nr:	153
Title:	Generic Architecture for Modular Real-time Systems in Robotics
Authors:	Thomas Schöpping, Timo Korthals, Marc Hesse and Ulrich Rückert
Abstract:	With the continuous progress in robotics and application of such systems in evermore scenarios, safety and flexibility become increasingly important aspects and new designs should thus emphasize real-time capability and modularity. This work points out all related topics for such an endeavor and proclaims to move from conventional bottom-up design to more holistic approaches. Based on experience gained with the modular mini robot platforms BeBot and AMiRo, a novel generic modular architecture is proposed that offers high flexibility and system wide real-time capability.
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Paper Nr:	155
Title:	Gain-Scheduling Position Control Approaches for Electromagnetic Actuated Clutch Systems
Authors:	Claudia-Adina Bojan-Dragos, Mircea-Bogdan Radac, Radu-Emil Precup, Elena-Lorena Hedrea, Alexandra-Iulia Szedlak-Stinean and Stefan Preitl
Abstract:	The paper proposes three Gain-Scheduling (GS) control design approaches dedicated to the position control of electromagnetic actuated clutch systems. The initial nonlinear mathematical model of the plant is simplified and next linearized at six operating points to use it in the design approaches. Starting with classical Proportional-Integral (PI) controllers, three GS control versions, namely Lagrange, Cauchy and Switching GS, are next designed to ensure zero steady-state control error and the switching between PI controllers. All control solutions are tested and validated on the nonlinear model of the plant and a comparative analysis is included.
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Paper Nr:	170
Title:	Toward an Accurate Hydrologic Urban Flooding Simulations for Disaster Robotics
Authors:	Marcelo Paravisi, Vitor A. M. Jorge and Alexandre Amory
Abstract:	Testing and benchmarking robots in actual disaster scenarios is risky and sometimes nearly impossible. The lack of adequate tests could make robots more vulnerable and less effective in an actual disaster situation. However, even if it was possible to test them in a disaster scenario, the test itself would have high risks for the equipment and the robot operator. For this reason, simulations can be a powerful alternative to validate unmanned systems in safe and controlled virtual environments. The main challenge is to devise an accurate virtual scenario as close as possible to an actual disaster scenario. This problem is particularly harder if the robot in question is an unmanned surface vehicle (USV), mainly due to the numerous disturbances which can affect the robot. This paper presents and discusses the simulation of an urban flooding scenario with accurate environmental disturbances faced by an USV, such as water currents, waves and winds. Results demonstrate that these environmental disturbances have a relevant effect on the USV’s ability to perform basic navigational tasks. The main conclusion of this work is that there is a long road ahead of USV simulators in order to validate USVs in realistic disaster scenario simulations.
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Paper Nr:	176
Title:	A Suboptimal Strategy for Autonomous Marine Vehicle Navigation in Variable Sea Currents
Authors:	Kangsoo Kim
Abstract:	A navigation strategy achieving suboptimality in the transits of autonomous marine vehicles is presented. The objective of optimal navigation is the minimum-time transit of a marine vehicle moving in a flow field of sea currents. Reactive revisions of an ongoing optimal navigation followed by tracking controls are the key features of the proposed suboptimal strategy. In this research, a globally working numerical procedure for obtaining the solution of an optimal heading guidance law is presented. The developed solution procedure derives optimal heading reference that achieves the minimum-time transit of a marine vehicle in any deterministic sea currents whether stationary or time varying. The proposed suboptimal navigation works as a fail-safe strategy for the optimal navigation when there happen significant hostile actions which possibly cause the failure in ongoing optimal navigation. Simplicity and robustness are notable characteristics of our suboptimal strategy compared to others seeking rigorous optimality. Simulation results of autonomous underwater vehicle routing conducted by suboptimal navigation in various sea currents are presented.
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Paper Nr:	187
Title:	Design of a Saw Cutting Machine for Wood and Aluminum
Authors:	Jawad Ul Haq, Ahmed Jawad Qureshi and Mohamed Al-Hussein
Abstract:	The intensive use of wood in furniture, building, bridges, and of aluminum in transportation and construction, underscores the economic importance of these building materials in North America. Power saws are very useful tools for cutting and shaping such materials; however, they can cause serious hand injuries. In a table saw operation for wood cutting, for instance, the operator’s hands are vulnerable as they are used to guide pieces into the saw. In addition, the saw operator faces the risk of material being kicked back out of the saw or of sustaining an eye or respiratory injury due to the presence of sawdust and other debris generating by the operation of the saw. Meanwhile, aluminum cutting requires careful precaution and accuracy. The cutting can be dangerous if not handled properly. The greatest challenge in this regard is securely holding the material being cut. Furthermore, industrial requirements such as pneumatics and three-phase power supply preclude the ready use of such machines on a domestic scale. The cutting capability of existing table saws is coupled in such a way that it cannot cut both wood and aluminum. In this paper, a concept of a saw cutting machine (SCM) is presented using Axiomatic Design to ensure design objectives such as safety, user comfort, usage on a domestic scale and capability to cut both types of materials. In the presented case study, the mapping from Customer Attributes (CAs) to Functional Requirements (FRs) and then respective Design Parameters (DPs) resulted in an uncoupled design, in turn leading to a detailed mechanical design followed by the control system, all based on the aforementioned design objectives.
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Paper Nr:	196
Title:	Mixed Energy Model for a Differential Guide Mobile Robot Evaluated with Straight and Curvature Paths
Authors:	Mauricio F. Jaramillo Morales and Juan B. Gómez Mendoza
Abstract:	Energy consumption is an important issue for mobile robots that carry a limited energy sources, like batteries, for a long period of time. An energy model can relate the kinematic movements of the robot with energy values, giving an estimation of the energy needed for the robot to fulfill a specific task. In this study an energy model is proposed, based on the dynamic parameters of the mobile robot, as well as the motors, given an energy value close to real energy consumption. Mixed energy model is tested with a well-known motor energy model, using the velocities related to straight and curvature paths as input. In the results, a higher energy consumption value is identified by the mixed energy model, especially when the acceleration of the mobile robot increases. Energy models are configured with P3-DX robot mobile parameters.
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Paper Nr:	201
Title:	Improving the Joint Mobility of Acute Rotator Cuff Injury by Portable Rehabilitation Device
Authors:	Laura Jiménez Guzmán, Mariana Torrente Rocha and Hernando Leon-Rodriguez
Abstract:	The incidence of shoulder pain in the general population is around 11.2 cases per 1,000 patients per year. It is considered to be the most prevalent soft tissue pathology, with an estimated incidence of rotator cuff injuries of 3.7 per 100,000 per year. The deterioration of the components of the rotator cuff is one of the most frequent causes of musculoskeletal pain and disability in the world. The conditions of the rotator cuff increase with the age and overuse of the joint, therefore, elderly patients are more affected. This paper presents the development of one soft and portable rehabilitation prototype robot that aims to be evaluated with patients in near future as a suitable device for rehabilitating acute rotator cuff injuries through clinical examinations. The portable robot presented was design from biomechanical analysis and ranges of kinematics and joint dynamics; aspects that determined important requirements for obtaining greater functionality of the prototypeś portability and with the identification of pre-set tasks that executes two types of specific movements: flexion / extension and external / internal rotation by means of a soft rehabilitation and portable robot device.
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Paper Nr:	203
Title:	Progression of Electronic and Communication System for Motion Control of Modular Snake-like-Robot
Authors:	Daniel Armando Gómez, Javier Camilo Torres Vera and Hernando León-Rodríguez
Abstract:	This Project consists of a development of an electronics system to manipulate a snake like robot in a modular way. The structure of this project is based on three topics; The Hardware and its Firmware, The Mathematical Analysis of the Serpenoid Curves and The Robotic Simulation. In regards to the first topic electronic cards were implemented in a master-slave relationship for joint control of each mechanical module, these cards are composed of a DSPIC30F4011, microchip 16-bit microcontroller that incorporates the CAN module, essential protocol for communication between cards, PWM outputs for motor control, analogue and digital ports; as well as a socket to connect to an external device through the UART. The firmware has been written in MikroC Pro. The mathematical analysis is based on the Hirose-Serpenoid curves, hence every microcontroller implements a characteristic equation from the Hirose curves to generate a serpentine movement and last but not least the snake like robot is simulated using ROS (Robotic Operating System) in Rviz.
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Paper Nr:	214
Title:	Autonomous Vehicle Steering Wheel Estimation from a Video using Multichannel Convolutional Neural Networks
Authors:	Arthur Emidio T. Ferreira, Ana Paula G. S. de Almeida and Flavio de Barros Vidal
Abstract:	The navigation technology in autonomous vehicles is an artificial intelligence application which remains unsolved and has been significantly explored by the automotive and technological industries. Many image processing and computer vision techniques allow significant improvements on such recent technologies. Using this motivation as a basis, this work proposes a novel methodology based on Multichannel Convolutional Neural Networks (M-CNN) capable of estimating the steering angle of an autonomous vehicle, having as only input images captured by a camera attached to the vehicle’s frontal area. We propose five Convolutional Neural Network architectures: 1-channel, 2-channel and 3-channel in the convolution step. Based on the performed tests using a public video dataset, it is presented a quantitative comparison between the proposed models.
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Paper Nr:	218
Title:	Development of a Robot for Boiler Tube Inspection
Authors:	Md. Hazrat Ali, Temirlan Zharakhmet, Mazghzhan Atykhan, Adil Yerbolat and Shaheidula Batai
Abstract:	The maintenance and inspection of large vertical or horizontal tubes in an autonomous manner is still an unsolved issue. Existing techniques can traverse various types of surfaces but cannot measure inner cracks in a long tube. However, most of these techniques are restricted by accuracy level, type of construction material and cost efficiency. This research is mainly focused on the studies of various types of design investigations related to the climbing robots for the inspections, and design and development of a new robot to solve the existing problem in measuring various pipes diameter in petroleum industries. Based on the existing prototypes, a new type of adhesion, locomotion, sensor mechanisms and a modernized design was accomplished. The importance of this work is to prevent hazardous failures, which probably can be determined through the on-site analyses of the tubes. At this point, it is a laborious, time-consuming and dangerous process, which is performed by the human being. Finally, a climbing robot based on duct fan is designed and developed as a prototype. The thrust force, provided by the fan, ensures that the robot is not falling while the DC motors generate the motion. The ultrasonic sensor is chosen for the defect detection. It generates a reference signal of a proper tube and compares it to the signals received from the defected tubes. The preliminary design and development of the robot are done in SolidWorks software together with the available components in the market.
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Paper Nr:	15
Title:	Control of the Chaotic Phenomenon in Robot Path using Differential Flatness
Authors:	Salah Nasr, Amine Abadi, Kais Bouallegue and Hassen Mekki
Abstract:	This paper deals with the complex chaotic behavior that can appear in the dynamic trajectory of a mobile robot, when the robot is broken or partly damaged. However, a flatness-based controller is designed to ensure the trajectory planning and tracking. Different mathematical tools have been used such as the flatness control technique and non linear chaotic systems. The simulation results for the kinematic controller are presented to demonstrate the effectiveness of this approach.
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Paper Nr:	35
Title:	Path Tracking with Orthogonal Parametrization for a Satellite with Partial State Information
Authors:	Wojciech Domski and Alicja Mazur
Abstract:	This article presents an orthogonal parametrization for a space robot. A simulation scenario was presented where a satellite with a fixed 2R planar manipulator arm is chasing a moving object in the space. A path tracking algorithm with partial state information such as distance to chased object and difference in orientation was used. Due to the undemanding nature of proposed algorithm the satelite can successfully chase an object with limited state information. The chase manoeuvre is divided into two stages. The first stage is to enter an orbit around the object while following curvilinear path. In turn, the second stage is to settle in a point on the orbit to create favourable conditions for any further operations.
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Paper Nr:	45
Title:	3D Face Recognition on Point Cloud Data - An Approaching based on Curvature Map Projection using Low Resolution Devices
Authors:	Luis Felipe de Melo Nunes, Caue Zaghetto and Flavio de Barros Vidal
Abstract:	Facial recognition is the most natural and common form of biometrics, routinely used by humans and one of the most promising areas in biometrics research. The majority of traditional researches and commercial use of facial recognition systems are focused on methods that explores 2D (two-dimensional) images of human faces. All of them are based on features extraction that does not use any 3D shape information from the faces, especially with regard to depth. This paper presents a method based on Point Cloud and Curvature Map Projection to perform a 3D face recognition. The achieved results are presented and divided in two test scenarios, composed by a biometric evaluation analysis applying the Equal Error Rate score, Receiver Operating Characteristic and an accuracy comparison with other related works. The proposed work presents an accuracy of about 98.92%, allowing it to be applied for 3D face recognition tasks.
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Paper Nr:	71
Title:	Multiple Collision Avoidance between Human Limbs and Robot Links Algorithm in Collaborative Tasks
Authors:	Leonardo Sabatino Scimmi, Matteo Melchiorre, Stefano Mauro and Stefano Pastorelli
Abstract:	In this paper a real-time collision avoidance approach useful for human-robot interaction was presented and tested. This approach is based on a collision avoidance algorithm and a distance calculation algorithm. The collision avoidance algorithm was developed to avoid possible collisions between the upper part of the human body and the links of the robot. The positions of 25 characteristic points of the body of the human operator are acquired by two vision sensors. The distances between the robot and the operator are evaluated with the proposed distance calculation algorithm. These algorithms permit a real-time control of a collaborative robot. The collision avoidance approach was tested with two kinds of experiments. The results of the tests are presented.
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Paper Nr:	83
Title:	Characteristics of a Mower Robot with Swing Mower Mechanism by Simulation
Authors:	Ryota Suzuki and Yoshihisa Uchida
Abstract:	This study proposes a new mower robot with a swing mower mechanism for advantages such as a string trimmer and a wide swath. The proposed swing mower mechanism is designed for installation in the main body of a four-wheel drive mower robot AMR-D01. The AMR-D01 had overall dimensions as follows: 0.60 m length, 0.50 m width, and 0.30 m height; it weighs 28 kg and maximum velocity is 1.29 m/s. The swing mower mechanism is based on the lever-crank mechanism and translates motor rotation into swing of the rotary blade. We model the mechanism and simulate the characteristics of the centroid movement, sideslip, energy consumption, and operation time to evaluate the swing mower mechanism. The robot velocity is controlled to prevent the occurrence of the unmown spot. Swath is increased from 0.24 m to 0.62 m by 2.58 using the mechanism. The operation time is also decreased by 1/2.58. The swing mower mechanism does not have much influence on the robot movement. The change of the static friction coefficient and the slope angle also does not have much influence on the sideslip of the robot under the present conditions. The energy consumption increases with the increasing robot velocity.
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Paper Nr:	105
Title:	Development of a Ground Truth Localization System for Wheeled Mobile Robots in Indoor Environments based on Laser Range-finder for Low-cost Systems
Authors:	Luis Piardi, José Lima and Paulo Costa
Abstract:	The localization systems are becoming more and more required in the actual flexible manufacturing systems based on mobile robots. There are several approaches to localize a mobile robot such as laser scanners reflective beacons, image mapping, lightning based systems, Ultra-wideband time-of-flight trilateration, odometry and fusion sensor data algorithms. During the development phase of a localization methodology, it is necessary to evaluate the proposed system: it is used a ground truth system. Ground truth systems are precise (usually based on reflective beacons) but expensive. This paper presents a low-cost ground truth system based on a standard low-cost laser scanner that, coupled with the presented algorithm, allows to localize the robot in the field and thus evaluate other localization systems. Results of the precision of the developed system are presented and validates the approach.
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Paper Nr:	120
Title:	Chaos Engineering and Control in Mobile Robotics Applications
Authors:	Salah Nasr, Amine Abadi, Kais Bouallegue and Hassen Mekki
Abstract:	This article briefly summarizes the theory of chaos and its applications. Firstly, we begin by describing chaos as an aperiodic bounded deterministic motion, which is sensitive to initial states and therefore unpredictable after a certain time. Then, fundamental tools of the chaos theory, used for identifying and quantifying chaotic dynamics, are shared. The paper covers a main numerical approach to identify chaos such as the Lyapunov exponents. Many important applications of chaos in several areas such as chaos in electrical and electronic engineering and chaos applications in robotics have been presented. An analysis of the reviewed publications is presented and a brief survey is reported as well.
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Paper Nr:	140
Title:	Atlas - Examining the Wider Context of Assistive Robotics
Authors:	H. D. Doran, S. Neumann, H. K. Becker, A. Kollmar, S. Misoch, C. Pauli, S. Müller and F. Hannich
Abstract:	We examine the proposition of a stationary assistive robot arm in the kitchen. Based on a preliminary business plan and with the aim of generating engineering requirements, a multi-disciplinary project was established to examine the wider ramifications of such assistive technology in the household, in a Swiss context, in the fields of health and social wellbeing. Additionally the engineering aspects as well as the business aspects were examined. We detail both the individual methodologies used in this study, the results achieved and discuss the results in a wider context.
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Paper Nr:	169
Title:	Preliminary Results for Secure Traffic Regulation
Authors:	Assia Belbachir, Sorore Benabid, Marcia Pasin and Amal El Fallah Seghrouchni
Abstract:	In this paper, we propose a solution for traffic regulation in Intelligent Transportation Systems (ITS). Due to the heterogeneity and dynamic nature of transportation networks, the big challenge is to be able to take the correct decisions to smooth the traffic flow. This decision is at the same time centralized within a Central Communication Coordinator (CCC) which is in charge of controlling the traffic lights and also distributed among the vehicles that are in the nearby of cross section. The decision should be made upon a permanent exchange of information between the vehicles and the CCC’s. Thus, an important issue is to ensure a robust and secure communication between the different components able to resist to hypothetic hacker’s attacks. The aim of this paper is to setup an intelligent system to regulate traffic flow taking into account different types of attacks. We show in this paper our simulated results using the client MATLAB together with the server SUMO (Simulation of Urban Mobility) so that client can access and modify the simulation environment. We simulated one intersection using an algorithm to regulate the traffic and explain our obtained results.
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Paper Nr:	183
Title:	Integrated Guidance, Navigation, and Control System for a UAV in a GPS Denied Environment
Authors:	Ju-Hyeon Hong, Chang-Kyung Ryoo, Hyo-Sang Shin and Antonios Tsourdos
Abstract:	This paper proposes an integrated guidance, navigation, and control system for operations of a UAV in GPS denied environments. The proposed system uses a sensor combination, which consists of an image sensor and a range sensor. The main idea of the system developed is that it replaces the conventional navigation information with the measurement from the image processing. For example, it is possible to substitute the look angle and look angle rate from the image sensor for the conventional navigation information like the relative target position and the body angular rate. As the preliminary study, the integrated guidance and control system is designed with a nonlinear back-stepping approach to investigate the possibility of the proposed system. And the proposed integrated guidance and control system is verified by the numerical simulation.
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Paper Nr:	185
Title:	The Hand-gesture-based Control Interface with Wearable Glove System
Authors:	Vladislav Berezhnoy, Dmitry Popov, Ilya Afanasyev and Nikolaos Mavridis
Abstract:	The paper presents an approach to building a gesture-based control interface with a wearable glove system and a real-time gesture recognition algorithm. The glove-based system is a wireless wearable device with hardware components, including Arduino Nano controller, IMU and flex sensors, and software for gesture recognition. Our gesture recognition methodology requires two stages: 1) Building a library of dynamic gesture models with the reference human gesture graphs; 2) Gesture capturing and evaluating with fuzzy c-means (FCM) clustering and constructing grammars of gestures by fuzzy membership functions. The system tests were provided with 6 different dynamic gestures to control position and orientation of a quadcopter in V-Rep simulator that has demonstrated encouraging results with a reasonable quality of real-time gesture-based quadcopter control.
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Paper Nr:	192
Title:	Initial Tuning Procedure for Attitude and Vertical Movement Controllers in Multirotor Aerial Vehicles with Heterogeneous Propulsion Units
Authors:	Przemysław Gąsior, Adam Bondyra and Stanisław Gardecki
Abstract:	In this paper, a hybrid procedure of tuning the control structure of a newly developed multirotor aerial platform is presented. Such situation presents a demanding task because there are no initial parameters of PID controllers ensuring safe flight conditions. Most methods base on full mathematical models which can be divergent from the real plant and require a process of detailed system’s identification. The second area of solutions utilises different types of test benches to perform trial and error tuning in safe conditions. A method presented in this article comprises a hybrid approach connecting both practices. The key element in this solution is a model of the implemented propulsion system and physical parameters of the airframe itself obtained from the CAD software. System noise variances are gathered from experiments on the test bench and implemented in appropriate simulations. Next, the optimisation can be executed to gather parameters for every constituent controller. Finally, verification in real conditions is performed. The presented method was used for the development of two significantly different multirotor UAVs during the pre-flight PID control tuning phase. An approach is versatile for both symmetrical and unsymmetrical heterogeneous airframes.
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Paper Nr:	200
Title:	Walking Robot Bio-inspired by Insect’s Locomotion for Carbon Dioxide Diagnostic Indexed in the Air
Authors:	Santiago Noriega Álvarez, María Camila Rojas and Hernando Leon-Rodriguez
Abstract:	The spiders, in comparison with the majority of others animals, it has the ability to access all kind of environment where others animals or even the humans can’t. Those attributes of the spiders are taken into this project in order to design and develop a quadruped spider robot with the ability to move in all kind of directions and perform pre-set motions programs such as ascend, descend, obstacles avoiding and gas detections. The paper is presented the dynamic and kinematics model with the purpose of understand how, mathematically the quadruped animal and spiders walk. In this sense we studied the movement of a real spider in order to define a suitable bio-mimetic locomotion model. In additions walking simulations were implemented and the gas detection results are presented.
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Paper Nr:	206
Title:	Dynamic Estimation of Visco-elastic Mechanical Characteristics of Biological Samples under Micro Manipulation
Authors:	Paolo Di Giamberardino, Maria Laura Aceto, Oliviero Giannini and Matteo Verotti
Abstract:	This paper focuses on the possibility of using a recently fabricated micro gripper for the on line estimation of the mechanical characteristics (damping and elasticity) of a sample pinched by the jaws, with particular reference to biological tissues. A classical on line dynamical parameter estimator is computed for the given system with different estimation computations, and its effectiveness has been verified by numerical simulations. Results confirm the feasibility of a micro-robotic clinical device for surgery use equipped with a tissue recognition ability.
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Paper Nr:	211
Title:	Boccia Court Analisys for Real-time Scoring
Authors:	Pedro Leite, Alexandre Calado and Filomena Soares
Abstract:	This paper aims to develop a tool to increase the engagement and commitment of the elderly population in the Boccia game. This tool is based on the implementation of a real-time computer vision algorithm that analyses the Boccia court field and displays the score in a graphical user interface. In Portugal, physical inactivity is associated with 14% of deaths per year, higher percentage than the world average, which is less than 10%. In this paper, the Boccia game is used for promoting physical activity in the elderly, due to its simplicity and adaptability to their physical impairments. This system intends to encourage the elders to lead a more active lifestyle, providing a healthier life and possibly reducing the risk of major diseases and injuries.
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Paper Nr:	216
Title:	Development of a Network-based Autonomous Firefighting Robot
Authors:	Md. Hazrat Ali, Sultan Shamishev and Aidos Aitmaganbayev
Abstract:	This paper presents the design and development of a prototype of network-based automated firefighting robot. It addresses the water-based extinguishing system for fire using the spray gun and pump. For this purpose, a mini car washer is used. Gas sensors are integrated to create network system to navigate robot to the target distance. The proper navigation depends on the algorithm of obstacle avoidance. Currently, fire extinguish become challenging especially in a multi-storey building. This work gives a solution to extinguish fire automatically to prevent danger in a residential premise. The prototype is built from the low-cost materials available at the laboratory.
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Area 4 - Signal Processing, Sensors, Systems Modelling and Control

Full Papers

Paper Nr:	58
Title:	Stability Analysis of a Regulated Oxygen Mask
Authors:	Geoffray Battiston, Dominique Beauvois, Gilles Duc and Emmanuel Godoy
Abstract:	We analyse the stability of a regulated oxygen mask distributing oxygen in response to an inhalation demand. The mask pressure exhibits troublesome vibrations after the demand reaches a certain flow value. Starting from a simple nonlinear model, we perform a local linear stability analysis which highlights that the real part of two eigenvalues is positive when this system is chattering. We propose then adjustments of some parameters of this purely mechanical system in order to avoid this phenomenon. These adjustments have been tested and validated experimentally.
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Paper Nr:	77
Title:	H∞ Measurement-feedback Tracking with Preview
Authors:	Eli Gershon
Abstract:	Finite-horizon H∞ output-feedback tracking control for linear discrete time-varying systems is explored along with the stationary infinite-horizon case. We consider three tracking patterns depending on the nature of the reference signal i.e : whether it is perfectly known in advance, measured on-line or previewed in a fixed time-interval ahead. For each of the above three cases a solution is found where, given a specific reference signal, the controller plays against nature which chooses the initial condition and the energy-bounded disturbances. The problems are solved based on a specially devised bounded real lemma for systems with tracking signals. The finite-horizon case is extended to the stationary one where similar results are achieved.
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Paper Nr:	87
Title:	Accurate Pose Estimation of a Hand-held RGBD Camera based on Sub-volume Matching for 3D Modeling
Authors:	Eung-su Kim and Soon-Yong Park
Abstract:	The smoothness of the result of full body 3D reconstruction, also known as 360◦ reconstruction using a single hand-held sensor depends on the accuracy of the pose estimation. In this paper, we present a new idea for accurate pose estimation of such a single hand-held RGBD sensor based on subvolumetric reconstruction. In our method, we first estimate initial pose of both RGB and depth sensors through 3D coarse registration. Thereafter, in the precision matching step, we select only the keyframes for matching and estimate relative pose between them based on registration refinement. If there is a large pose estimation error between the keyframes, a subvolume is constructed using data of adjacent frames of each keyframe, and refine the final relative pose between keyframes using subvolume estimations. A series of 3D reconstruction experiments are preformed to evaluate the accuracy of the estimated pose.
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Paper Nr:	94
Title:	State Feedback Optimal Control with Singular Solution for a Class of Nonlinear Dynamics
Authors:	Paolo Di Giamberardino and Daniela Iacoviello
Abstract:	The paper studies the problem of determining the optimal control when singular arcs are present in the solution. In the general classical approach the expressions obtained depend on the state and the costate variables at the same time, so requiring a forward-backward integration for the computation of the control. In this paper, sufficient conditions on the dynamics structure are provided and discussed in order to have both the control and the switching function depending on the state only, so simplifying the computation avoiding the necessity of the backward integration. The approach has been validated on a classical SIR epidemic model.
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Paper Nr:	101
Title:	Tracking Control of Electro-pneumatic Systems based on Petri Nets
Authors:	Carlos Renato Vázquez, José Antonio Gómez-Castellanos and Antonio Ramírez-Treviño
Abstract:	This work introduces and solves a tracking control problem for electro-pneumatic systems (ENS) modeled by interpreted Petri nets (IPN). The aim of this work is to maintain the simplicity of the specifications given by practitioners in the field of ENS’s and formalize the synthesis of a controller to ensure properties such as controllability, liveness and boundedness. In order to achieve this goal, this work presents the IPN models for ENS elements. The synchronous product of these modules yields in the plan model. Afterwards the synthesis of the controller is presented as an algorithm that provides both an IPN model of the closed-loop system and an IPN model of the controller, which can be translated to a Ladder Diagram for its implementation on a PLC device. The method is applied to a small ENS to show its efficacy.
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Paper Nr:	108
Title:	Multi–level Identification of Hammerstein–Wiener (N–L–N) System in Active Experiment
Authors:	Marcin Biegański
Abstract:	The paper addresses the problem of Hammerstein–Wiener (N–L–N) system identification. The proposed strategy embraces two-experiment approach to the system identification, in which system is excited with random process in passive experiment and with binary process in active experiment. The proposed approach uses both parametric (least squares) and nonparametric (kernel estimates) identification tools. It consists of four consecutive stages, where linear dynamic and nonlinear static parts of the system are identified separately. Output nonlinearity estimation is executed under active experiment. The consistency of the estimate is analyzed and simple simulation example is presented.
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Paper Nr:	123
Title:	Nonlinear Adaptive Estimation by Kernel Least Mean Square with Surprise Criterion and Parallel Hyperslab Projection along Affine Subspaces Algorithm
Authors:	Angie Forero and Celso P. Bottura
Abstract:	In this paper the algorithm KSCP (KLMS with Surprise Criterion and Parallel Hyperslab Projection Along Affine Subspaces) for adaptive estimation of nonlinear systems is proposed. It is based on the combination of: - the reproducing kernel to deal with the high complexity of nonlinear systems; -the parallel hyperslab projection along affine subspace learning algorithm, to deal with adaptive nonlinear estimation problem; - the kernel least mean square with surprise criterion that uses concepts of likelihood and bayesian inference to predict the posterior distribution of data, guaranteeing an appropriate selection of data to the dictionary at low computational cost, to deal with the exponential growth of the dictionary, as new data arrives. The proposed algorithm offers high accuracy estimation and high velocity of computation, characteristics that are very important in estimation and tracking online applications.
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Paper Nr:	133
Title:	18O Isotope Concentration Control
Authors:	Valentin Sita, Vlad Mureşan, Mihail Abrudean, Mihaela-Ligia Ungureşan and Iulia Clitan
Abstract:	The paper presents a solution to control the 18O isotope concentration at the output of a separation column. The proposed mathematical model which describes the work of the separation column is a distributed parameter one and it approximates with high accuracy the work of the real plant. The isotope separation process is included in a complex control structure which generates high control performances. In order to improve significantly the separation column productivity, an original solution for the efficient rejection of the disturbances effects, is proposed. Also, a solution to determine the instantaneous value of the separation column length constant is proposed, solution which opens the possibility to implement new control strategies.
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Paper Nr:	137
Title:	Indoor Target Tracking using Time Difference of Arrival Measurements in 3D
Authors:	Yifan Xie, Seung Hyo Park and Taek Lyul Song
Abstract:	Target tracking with time difference of arrival measurements usually encounters the problem of correlated measurement noises. When the sensor network utilizes the common reference sensor, the covariance matrix of the correlated measurement noises becomes off-diagonal such that the computational complexity of the inverse of the covariance matrix as well as the subsequent matrix operations increases proportionally to the cube of the sensor number. This makes target tracking algorithms inconvenient for practical applications, and an appropriate measurement noise decorrelation method is required. In multi-sensor environments, the parallel update and the serial update are applied for exploiting the measurements from different sensors. Although the two methods deliver the equivalent tracking performances in linear systems, this equivalence does not hold in nonlinear systems as linearizing the nonlinear functions leads to approximation error. Additionally, the requirements of the two methods for storage structure and computational resource allocations are different. This paper presents a target tracking algorithm which integrates the Cholesky decomposition to decorrelate the measurement noises for the serial update which shows computational efficiency. The tracking performance is evaluated by estimation accuracy, execution time.
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Paper Nr:	219
Title:	Approximate Recursive Bayesian Estimation of State Space Model with Uniform Noise
Authors:	Lenka Pavelková and Ladislav Jirsa
Abstract:	This paper proposes a recursive algorithm for the state estimation of a linear stochastic state space model. A model with discrete-time inputs, outputs and states is considered. The model matrices are supposed to be known. A noise of the involved model is described by a uniform distribution. The states are estimated using Bayesian approach. Without using an approximation, the complexity of the posterior probability density function (pdf) increases with time. The paper proposes an approximation of this complex pdf so that a feasible support of the posterior pdf is kept during the estimation. The state estimation consists of two stages, namely the time and data update including the mentioned approximation. The behaviour of the proposed algorithm is illustrated by simulations and compared with other methods.
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Short Papers

Paper Nr:	41
Title:	Cubature Kalman Filter-based Performance Enhancement of Wireless Indoor Localization using Ultra-wideband
Authors:	Seong Yun Cho
Abstract:	Ultra-wideband has been widely used for accurate wireless indoor localization systems due to accurate ranging measurement capability. There are several methods for ranging-based localization systems: iterative methods, linear closed-form solutions, model-based filters, etc. These methods have their advantages and disadvantages. In this paper, the characteristics of these methods are analysed and a cubature Kalman filter-based localization method is presented to improve the localization performance in various indoor environments.
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Paper Nr:	52
Title:	A New Device for Hydrogen Production on Demand with Application to Electric Assist Bike: Description, Production Characteristics and Basic Control
Authors:	Jocelyn Sabatier, Fabrice Mauvy, Jean-Louis Bobet, Damien Mohedano, Matthieu Faessel and Frédéric Bos
Abstract:	Using a magnesium-based hydrolysis reaction that spontaneously produces hydrogen with a high kinetic and a high efficiency, this paper proposes a solution to supply a PEM fuel cell that permits production on demand. This solution is an instrumented reactor that uses capsules with magnesium powder and that controls the hydrolysis reaction in order to maintain a constant pressure. The hydrogen produced by the reactor is used to feed a PEM fuel cell in which variable electric loads are applied. By solving both the hydrogen supply and storage problems, such a system is particularly suitable for light mobility applications.
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Paper Nr:	63
Title:	A Novel Big-data-based Estimation Method of Side-slip Angles for Autonomous Road Vehicles
Authors:	Dániel Fényes, Balázs Németh and Péter Gáspár
Abstract:	In the paper a novel side-slip estimation algorithm, which is based on big data approaches, is proposed. The idea of the estimation is based on the availability of a large amount of information of the autonomous vehicles, e.g. yaw-rate, accelerations and steering angles. The significant number of signals are processed through big data approaches to generate a simplified rule for the side-slip estimation using the onboard signals of the vehicles. Thus, a subset selection method for time-domain signals is proposed, by which the attributes are selected based on their relevance. Furthermore, a linear regression using the Ordinary Least Squares (OLS) method is applied to derive a relationship between the attributes and the estimated signal. The efficiency of the estimation is presented through several CarSim simulation examples, while the WEKA data-mining software is used for the OLS method.
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Paper Nr:	103
Title:	Finite-Time Altitude and Attitude Tracking of a Tri-Rotor UAV using Modified Super-Twisting Second Order Sliding Mode
Authors:	Yassine Kali, Jorge Rodas, Maarouf Saad, Khalid Benjelloun, Magno Ayala and Raul Gregor
Abstract:	This paper presents the problem of robust altitude and attitude trajectory tracking of a tri-rotor Unmanned Aerial Vehicle (UAV) based on a finite-time second order sliding mode control algorithm. The chosen algorithm is a modified super-twisting control with double closed-loop feedback regulation that provides fast finite-time convergence even when the system trajectories are far from the sliding surface, robustness against a wide class of uncertainties and disturbances. Moreover, this algorithm eliminates the major disadvantage of the classical sliding mode, the well-known chattering phenomenon. The stability analysis of the closed-loop system and the convergence time are given based on a strong Lyapunov function. To show the effectiveness of the used method, simulation results of different scenarios are presented for the considered tri-rotor UAV.
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Paper Nr:	110
Title:	An Improved Robust Adaptive Control Design for a Flexible Transport Aircraft: LMI Approach
Authors:	Iman S. Delshad
Abstract:	This paper presents an improved robust adaptive control design for longitudinal dynamics of a large transport aircraft with flexible structure. The proposed adaptive control technique is consist of a baseline Linear Quadratic Gaussian (LQG) controller and a robust adaptive loop. Based on a Lyapunov functional, LMI-based adaptation laws are provided. Finally, the proposed robust adaptive control design is illustrated by implementing on a well-known large transport aircraft model with flexible structure. The performance of the designed controller will be compared with its rivals in literature from different angles such as complexity of the control structure and performance.

Paper Nr:	114
Title:	Recursive Identification of Continuous Time Variant Dynamical Systems with the Extended Kalman Filter and the Recursive Least Squares State-Variable Filter
Authors:	Flávio Luiz Rossini, Guilherme Santos Martins, João Paulo Silva Gonçalves and Mateus Giesbrecht
Abstract:	In this paper, a method for the continuous time varying dynamical systems identification is presented. The study is based on the integration of the State-Variable Filter (SVF), the Extended Kalman Filter (EKF) and the Recursive Least Squares State-Variable Filter (RLSSVF). The main contribution of the algorithm applied in this paper is that a state space continuous time model can be estimated based on the system sampled inputs and outputs. To validate the method, a continuous time varying benchmark system is simulated and the benchmark parameters are compared to the estimated model parameters. The benchmark outputs are also compared to the model outputs to verify the accuracy of the proposed method. The results obtained show that the model reproduces the benchmark behavior accurately.
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Paper Nr:	118
Title:	State Space Identification Algorithm based on Multivariable Impulse Response
Authors:	Mateus Giesbrecht, Gilmar Barreto and Celso Pascoli Bottura
Abstract:	In this paper the definitions of multivariable discrete impulse and multivariable discrete impulse response are clearly stated and explored. From these definitions, two methods to determine the Markov parameters of a multivariable linear system from input and output data are described. Combining any of the methods to a known method to determine the state space model matrices from the Markov parameters, a practical algorithm to determine state space models from input and output data is obtained. The algorithm is then implemented and compared to a known subspace identification algorithm. The main contributions of this paper are the explicit definitions of multivariable discrete impulse and multivariable discrete impulse response, the discussion of these concepts and the application of them to solve the multivariable linear system identification problem.
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Paper Nr:	146
Title:	Condition Monitoring of Electrolytic Capacitors via ESR Estimation with Recursive Least Squares and Sliding Mode Techniques
Authors:	J. M. Andrade
Abstract:	A new on-line electrolytic capacitor condition monitoring approach based on sliding mode concepts and the recursive least squares (RLS) with constant forgetting factor algorithm is proposed in this paper. This scheme involves robust exact differentiation which outperforms the classical differentiator based on linear approximations, when the system is affected by noise. The condition monitoring approach proposed in this paper allows for on-line estimation of the ESR which is considered to be one of the best indicators of capacitor degradation. Computer simulation results, considering a DC-DC buck converter, provide evidence of the effectiveness of the capacitor condition monitoring scheme proposed in this paper.
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Paper Nr:	150
Title:	Design and Characterization of a Plug-in Device for Tactile Sensing
Authors:	Go Otsuka, Masato Niwa, Toshio Kawanishi and Goro Obinata
Abstract:	Although the most of the functions of the human upper body can be performed by robotic technologies which are already developed, the hand and finger functions cannot be achieved by artificial alternatives, particularly concerning the dexterous manipulation. One of the reasons is the lack of tactile sensors like the ones observed in the human fingertip. The purpose of this paper is to design a vision-based tactile sensor with the size of a fingertip, and valuated it under several conditions of contact. The resolution performance of the developed vision-based sensor for measuring contact force and contact moment is shown based on preliminary experiments. Moreover, the results of these experiments show the potential of the proposed sensor for evaluating adhesive surfaces.
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Paper Nr:	163
Title:	An LSTM-based Descriptor for Human Activities Recognition using IMU Sensors
Authors:	Sara Ashry, Reda Elbasiony and Walid Gomaa
Abstract:	In this article, we present a public human activity dataset called ‘HAD-AW’. It consists of four types of 3D sensory signals: acceleration, angular velocity, rotation displacement, and gravity for 31 activities of daily living ADL measured by a wearable smart watch. It is created as a benchmark for algorithms comparison. We succinctly survey some existing datasets and compare them to ‘HAD-AW’. The goal is to make the dataset usable and extendible by others. We introduce a framework of ADL recognition by making various pre-processing steps based on statistical and physical features which we call AMED. These features are then classified using an LSTM recurrent network. The proposed approach is compared to a random-forest algorithm. Finally, our experiments show that the joint use of all four sensors has achieved the best prediction accuracy reaching 95.3% for all activities. It also achieves savings from 88% to 98% in the training and testing time; compared to the random forest classifier. To show the effectiveness of the proposed method, it is evaluated on other four public datasets: CMU-MMAC, USC-HAD, REALDISP, and Gomaa datasets.
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Paper Nr:	188
Title:	Parametric Sensitivity Analysis of a Multiple Model Adaptive Predictive Control for Regulation of Mean Arterial Blood Pressure
Authors:	Humberto A. Silva, Celina P. Leão and Eurico A. Seabra
Abstract:	Postsurgical complication of hypertension may occur in cardiac patients. To decrease the chances of complication it is necessary to lower high blood pressure as soon as possible. Continuous infusion of vasodilator drugs, such as sodium nitroprusside (Nipride), would quickly lower the blood pressure in most patients. However, each patient has a different sensitivity to infusion of Nipride. The parameters and the time delays of the blood pressure control system are initially unknown. Moreover, the parameters of the transfer function associated with a particular patient change over time. The objective of the study is to develop a procedure for blood pressure control in the presence of uncertainty of parameters and considerable time delays. In this paper, a sensitivity analysis was performed, changing the parameter that controls the convergence rate of weight factors (V). The simulation results showed significant changes in settling time (Ts), stressing the importance of this parameter on the control model definition. Considering a V = 0.05 was obtained Ts = 195s and, for same patient, Ts = 510s by increasing the value to V = 0.4, with the Root Mean Square Error (RMSE) varying but always lower than 1%.
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Paper Nr:	202
Title:	Robust Tube for Tracking Normal Function Pattern of Lower Urinary Tract Dysfunction Subject to Parameter Variations and Bounded Disturbance
Authors:	Jean Thomas
Abstract:	In (Thomas and Gomma, 2017) a treatment of neurologic Lower Urinary Tract (LUT) dysfunction is developed, where a closed-loop controller using Model Predictive Control (MPC) is proposed. The proposed controller shows its ability in controlling the micturition process and bringing the bladder behavior to its normal function pattern. Moreover, the obtained results in (Thomas and Gomma, 2017) demonstrate the controller robustness against limited system uncertainties. However, especially, considering the human body uncertainties, the question is till which limit the controller is robust? And does the controller guarantee the reference tracking in coexist of model mismatch and/or external disturbances. In this paper a robust tube centered around the reference trajectory is proposed using a polyhedral approach. The LUT model is assumed to be affected by parameter variations and bounded disturbances. A polyhedral approach is developed for which a robust control is assured to keep the system response within the robust tube despite the possible disturbance and the parameter variations. At each step, the maximal set in the output space from which output signals can be driven to the target region while taking into account the system uncertainties and the system constraints is computed using a geometrical approach. These computed sets and regions can be included into MPC constraints to guarantee the system evolution within the robust tube.

Paper Nr:	205
Title:	A Trajectory Controller for Kite Power Systems with Wind Gust Handling Capabilities
Authors:	Manuel C. R. M. Fernandes, Gonçalo B. Silva, Luís Tiago Paiva and Fernando A. C. C. Fontes
Abstract:	In this paper, we address the generation of electrical power using Airborne Wind Energy Systems, comprising a kite connected through a tether to a generator on the ground. We design a controller to steer the kite to follow a pre-defined periodic path, which includes a production mode, a tether retrieval mode, and a safe mode capable of handling wind gusts.
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Paper Nr:	209
Title:	A Novel Easy-to-construct Power Model for Embedded and Mobile Systems - Using Recursive Neural Nets to Estimate Power Consumption of ARM-based Embedded Systems and Mobile Devices
Authors:	Oussama Djedidi, Mohand A. Djeziri, Nacer K. M’Sirdi and Aziz Naamane
Abstract:	This paper features a novel modeling scheme for power consumption in embedded and mobile devices. The model hereafter presented is built thought data fitting techniques using a NARX nonlinear neural net. It showcases the advantages of using a nonlinear model to estimate power consumption over the widely used linear regression models, where The NARX neural net is simpler, easier to implement, and more importantly more suitable as power changes are not always linear. Finally, experimental results validate the model with one with an accuracy of 97.1% on a smartphone.
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Paper Nr:	36
Title:	Target Acquisition Systems - Suitability Assessment based on Joint Fires Observer Mission Criteria Determination
Authors:	Ivan Jan, Silinger Karel and Potuzak Ladislav
Abstract:	Article focuses on the artillery target acquisition systems in the context of properties required for the operations of joint fires observers (JFO). The aim of the article is to determine the optimal type (variant) of the target acquisition system for equipping the joint fires observers. The choice of the optimal type (variant) is based on the evaluation of properties of the currently employed artillery target acquisition systems in the Czech Army in relation to the requirements for operation of the joint fires observers. The partial objective of the article is to illustrate, using decision criteria, the requirements for the artillery target acquisition systems in accordance with the activities of joint fires observer. Additionally, the need for shift from magnetic orientation to gyroscopic orientation is highlited and illustrated by the experiment conducted during the assesment. The result of the article is the selection of the optimal type (variant) of target acquisition system for joint fires observer in accordance to currently employed systems, so the logistics flow will remain the same.
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Paper Nr:	74
Title:	Dynamic Analysis of the Fractional PID Controller
Authors:	Juliana Tonasso Herdeiro and Renato Aguiar
Abstract:	This article presents as main objective the study and application of the fractional PID controller in a positioning system, a controller that has basis on the fractional calculus theory originated in 1695 and, despite having generated several paradoxes in the decade, nowadays there are important applications of this theory, as the one reported in this paper. Initially, the controller will be designed by means of computational simulation for the nominal model of a plant, using a program in Matlab and optimization algorithms and, then, applying in a real process using a data acquisition technique in order to analyse its dynamic behavior in the presence of real external disturbances. Given that the fractional PID is a generalization of the traditional PID, the goal is to obtain, in practice, the benefits of this one in relation to the another, mainly observing the requirements of robustness and stability that must be present in the system.
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Paper Nr:	111
Title:	A Procedure to Generate Discrete MIMO Closed-loop Benchmark Via LFT with Application to State Space Identification
Authors:	Jorge A. Puerto Acosta and Celso P. Bottura
Abstract:	In this paper we use the conformal transformation known as linear fractional transformation (LFT), with the purpose of generating a discrete multivariable closed-loop benchmark from continuous multivariable closed-loop control system, having in mind state space identification. To reach this objective we propose a procedure based on the general framework representation (GFR) and on the multi input multi output (MIMO) LFT bilinear discretization process. We first use the LFT tool to obtain the continuous joint control-output (augmented) system form for representing the canonical closed-loop continuous system. Afterwards, we discretize the augmented continuous closed-loop system in order to obtain an augmented discrete model, then, we calculate the discrete plant and controller in the state space form. An application to the multivariable control of a continuous chemical reactor is presented and also we use the discrete benchmark generated to identify a state space model an example of the potential of the our proposal.
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Paper Nr:	148
Title:	Anomaly Detection using System Identification Techniques
Authors:	Gheorghe Sebestyen and Anca Hangan
Abstract:	As cyber-physical systems are becoming more human independent any anomaly or system failure should be detected and solved in an autonomous way. In the last decade significant research was performed to find more intelligent and accurate anomaly detection methods. Most of these methods are analyzing only the output(s) of a system hoping to find some inconsistencies in the data stream. Our attempt is to consider the system’s model as well and develop an anomaly detection methodology that tries to identify slight changes in the behavior of the system, detectable through model changes. The key part of our detection method is the system identification step through which we compute the system’s model considered as a differential equation between input and output signals or as an autoregression formula. We demonstrate the feasibility of the proposed method through a simulated and a real-life example.
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Paper Nr:	181
Title:	N4SID-VAR Method for Multivariable Discrete Linear Time-variant System Identification
Authors:	Alexander E. Robles and Mateus Giesbrecht
Abstract:	In this paper, a method for multivariable discrete linear time-variant system identification is presented. This work is focused on slowly multivariable time-variant systems, so that it is possible to define time intervals, defined as windows, in which the system can be approximated by time-invariant models. In each window, a variation of N4SID that uses Markov parameters is applied and a state space model is estimated. For that reason the proposed method is defined as N4SID-VAR. After obtaining the models for all windows, the error between system model outputs are calculated and compared to the system outputs. The N4SID-VAR was tested with a time-variant multivariable benchmark and the results were accurate. The proposed method was also compared to the MOESP-VAR method and, for the tested benchmark, the N4SID-VAR was faster and more accurate than the MOESP-VAR algorithm.
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Paper Nr:	195
Title:	Design of a Novel Six-Axis Force/Torque Sensor based on Optical Fibre Sensing for Robotic Applications
Authors:	Jun Huang, Chu Yan Wong, Duc Truong Pham, Yongjing Wang, Chunqian Ji, Shizhong Su, Wenjun Xu, Quan Liu and Zude Zhou
Abstract:	Force and torque information is critical to enabling intelligent control of a robot in complex robotic applications. This paper presents a novel six-axis force/torque sensor based on optical fibre sensing for robotic applications in extreme environments with intense electromagnetic interference as well as explosive and inflammable materials. The designed sensor employs an elastic sensing element composed of 4 compliant beams and 4 elastic cross beams to convert the measured forces and torques to the strain on the surfaces of elastic cross beams, which is detected by 16 Fibre Bragg Gratings (FBGs). The strain is calculated by theoretical analysis using Timoshenko beam theory and validated by Finite Element Analysis (FEA). Working matrix of the sensor is constructed, which is associated with the relationships between the measured forces and torques and the wavelength shifts of FBGs. The sensitive coefficients obtained by theoretical analysis and FEA simulation are in good agreement, which indicates that the analytical method is accurate. The proposed six-axis force/torque sensor with low cost and high reliability has great potential in robotic applications in harsh industrial environments.
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