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Keynote Lectures

Formation Control and Vision based Localization of System of Mobile Robots
Krzysztof Kozlowski, Poznan University of Technology, Poland

Controlled Magnetic Bearings for Smart Machines
Gerhard Schweitzer, ETH Zurich, Switzerland

Mobile Manipulation - Why Are Humans so Much Better? And How Can We Change That?
Oliver Brock, TU Berlin, Germany

Rough Terrain Mobile Robotics - From Design to Motion Control and Planning
Faïz Ben Amar, Université Pierre et Marie Curie, Institut Systèmes Intelligents et de Robotique, France

 

Formation Control and Vision based Localization of System of Mobile Robots

Krzysztof Kozlowski
Poznan University of Technology
Poland
 

Brief Bio

Professor K. Kozlowski received the M.S. degree in electrical engineering from Poznan University of Technology (PUT), Poland; and the Ph.D. degree in control engineering from PUT in 1979, where he is currently a full professor of robotics and automation. He joined the IEEE in 1983 and has been a Senior Member since 1988. He is the author of a book titled Modelling and Identification in Robotics (Springer-Verlag, 1998). He was and is on the editorial boards of several Polish and international journals (e.g. IEEE Robotics and Automation Magazine, IEEE Transactions on Control Systems Technology, Journal of Applied Mathematics and Computer Science, Journal of Intelligent Robotic Systems, Control Society Conference Editorial Board). He has served every year since 1995 on the ICRA Program Committee. He has worked as a program chair of the International Conference on Advanced Robotics (ICAR), 2001, International Workshop on Robot Motion and Control (RoMoCo) since 2001, and vice chairman of the IEEE Conference on Models in Automation and Robotics (MMAR), since 2001. In 2001 he was elected as a Chairman of the IEEE Robotics and Automation Chapter in Poland. The IEEE Robotics and Automation Society, Poland Section Chapter, was granted 2001 Chapter of the Year Award for the first time of history of the IEEE R$A. In 2014 he was reelected as chair of the IEEE Robotics and Automation Chapter in Poland. He is a member of the Control Systems Society Chapter in Poland. He has served as an RAS Administrative Committee member from 2000 till 2002 and 2004 till 2005. He served IEEE Control Systems Society as a member of Board of Governors in 2002 and 2003. He is also a member of EUROMECH, European Mechanics Society, since 1994 and GAMM, Geselschaft fur Angewandte Mathematik und Mechanik, since 1992. His control interest is in control of nonholonomic systems, multi-agent systems and application of robotic systems in particular in medicine and rehabilitation.


Abstract

In this presentation we give an overview of different control algorithms designed for both set point and trajectory tracking problems for a set of mobile robots moving in environment with static obstacles.  An arbitrary number of robots and obstacles can be used. 

Two new control algorithms are proposed. One is designed at the kinematic level and the second one at the dynamic level. It is assumed that we know all kinematical and dynamical parameters of robots. They can be different for all units which are used to build formation. Control scheme proposed at the kinematical level is based on a novel Vector Field Orientation (VFO) feedback control method developed in the Chair of Control and Systems Engineering with applications to a differentially-driven vehicle. We describe the control concept and control design methodology which originates from simple geometrical interpretations connected with the vehicle model structure. Novelty of the VFO method allows treating two considered control tasks – trajectory tracking and point stabilization – in a unified manner. Control system with VFO controllers reveal several practically desirable features like fast and non-oscillatory error convergence, simple interpretation of control inputs effect and, as a consequence, particular simplicity of the controller parametric synthesis. A new Lyapunov function candidate is proposed which takes into account control objectives and obstacle avoidance. It is shown that the proposed control algorithm is globally asymptotically stable to a small ball with radius which can be made arbitrary small.  Next this result is extended to the case when dynamics of robots is taken into account using standard back-stepping technique. Numerical stability and robustness to potential functions high values near robots and obstacles are very important issues which are widely discussed along with  computational complexity of all algorithms and their comparison with existing computational schemes. It is shown that increasing number of robots does not change computational burden significantly. Robots avoid obstacles both static and dynamic, in the case moving robots. It is shown how to avoid saddle points which are associated with obstacles in a set point control problem.

Theoretical considerations are supported by simulation results which are widely discussed. Next experimental work is presented and it clearly illustrates theoretical considerations. The multi-robot test-bed that was designed and implemented in the Chair of Control and Systems Engineering at Poznan University of Technology and uses vision-based localization. The camera is located above the task space and active LED markers are mounted on the top of differentially driven mobile robots. The image form the camera is transmitted to the vision server that identifies markers and stores their positions and orientations in the array. Then the resulting array is broadcasted to the robots with UDP packets. The data can be used to control the multi-robot system. Unsolved problems of control of multi agent systems are outlined at the end of presentation.



 

 

Controlled Magnetic Bearings for Smart Machines

Gerhard Schweitzer
ETH Zurich
Switzerland
 

Brief Bio
G.S. received his education as a mechanical engineer and his doctoral degree at the University Stuttgart, and his habilitation at the Technical University Munich, Germany. He had been working for research institutes and universities (DLR Oberpfaffenhofen, University Stuttgart, TU Munich, NASA Marshall Space Flight Center Huntsville) for 16 years before joining, in 1978, the ETH Zurich (Swiss Federal Institute of Technology) as a Professor for Mechanics. In 1989 he became Head of the Institute of Robotics and of the International Center for Magnetic Bearings at the ETH. In 1988 he chaired the First International Symposium on Magnetic Bearings. He was a founding member of the Mechatronics Group, of the Neuro-Informatics Group, and of the Nano-Robotics Project at the ETH. He was head of the Department of Mechanical Engineering and Production. He was a visiting professor at Stanford University, USA, at Campinas and at Florianopolis, Brazil, and at the ZiF of the University Bielefeld, Germany. His research interests include the dynamics of controlled mechanical systems, especially interactive robots, magnetic bearings and mechatronics. He is a member of the Swiss Academy of Technical Sciences. After retiring from official duties at the ETh, he founded a private Mechatronics Consulting. During 2003/04 he was appointed chair professor at Tsinghua University, Beijing, at the Institute of Novel and Nuclear Energy Technology. He is at home in Brazil and Switzerland.


Abstract
Controlled or Active Magnetic Bearings (AMB) keep a rotor in a hovering position, without any contact, with no wear or lubrication. They are a typically mechatronic product, combining mechanical design, electronics, and information processing. The lecture gives a short survey on function and history, and then concentrates on industrial applications and actual research challenges. The main application area is turbo-machinery, with power ranges up to 20 MW and more. Recent examples are shown. The research topics include control aspects, reliability and safety issues, and demonstrate the ability of AMB as a component of smart machinery. A machine is being called smart if it makes best use of the internal informations about its state to improve its performance. The sensor data of the AMB are very useful as well for obtaining information about the machine process itself and they can be used for external data mining within the objectives of Industry 4.0 projects.



 

 

Mobile Manipulation - Why Are Humans so Much Better? And How Can We Change That?

Oliver Brock
TU Berlin
Germany
 

Brief Bio
Oliver Brock is the Alexander von Humboldt Professor of Robotics in the School of Electrical Engineering and Computer Science at the Technische Universität Berlin in Germany. He received his Diploma in Computer Science in 1993 from the Technische Universität Berlin and his Master's and Ph.D. in Computer Science from Stanford University in 1994 and 2000, respectively. He also held post-doctoral positions at Rice University and Stanford University. Starting in 2002, he was an Assistant Professor and Associate Professor in the Department of Computer Science at the University of Massachusetts Amherst, before to moving back to the Technische Universität Berlin in 2009. The research of Brock's lab, the Robotics and Biology Laboratory, focuses on autonomous mobile manipulation, interactive perception, grasping, manipulation, soft hands, interactive learning, motion generation, and the application of algorithms and concepts from robotics to computational problems in structural molecular biology. He is also the president of the Robotics: Science and Systems foundation.


Abstract
There is a significant performance gap between human agents and robotic agents.  Closing this gap has been the goal or robotics research for many years now.  There are different opinions on how much progress the community as a whole has made in this regard.  In this talk, I would like to speculate on characteristics of solutions capable of closing that gap --- as opposed to the development of increasingly competent skills that serve specific applications but do not achieve the generality required to be part of closing the gap.  I will propose several characteristics and support their importance with experiments from the areas of grasping, interactive perception, and learning from interaction.  As these experiments can only be considered circumstantial evidence for my claims, I prefer to refer to these characteristics as “tricks”.  But my hope is, of course, that these tricks will develop into foundational components for the generation of versatile autonomous robot behavior.



 

 

Rough Terrain Mobile Robotics - From Design to Motion Control and Planning

Faïz Ben Amar
Université Pierre et Marie Curie, Institut Systèmes Intelligents et de Robotique
France
 

Brief Bio
Ziad ZAMZAMI was born in Egypt in 1987. He has received his B.S degree in mechanical engineering from the French University of Egypt In 2010 (Top of his class), as well as Master’s degree in material science from the Haute Alsace University, France, in the framework of a double degree program. In 2012, he received MSc degree in advanced systems and robotics from the University of Pierre and Marie Curie (Sorbonne Universités). He is currently pursuing the Ph.D. degree in the Institute of Intelligent Systems and Robotics, affiliated with University of Pierre and Marie Curie (Sorbonne Universités), Paris, France. He has participated in several national projects in France including fast autonomous rover and tracked mobile manipulation in collaboration with the french atomic energy commission and industrial partners. His current research interests include dynamic system modelling, autonomous mobile robots, mobile manipulation, skid steering and tracked vehicles.


Abstract
Rough terrain robotics is a new emerging research field that has stimulated a high number of works during recent years with the aim to provide more autonomy for outdoor vehicles. The talk will discuss the critical role of design and control in the development of autonomous off-road mobile robot. We will focus on articulated wheeled structure and particularly hybrid wheeled-legged locomotion, and show how they can be useful for autonomous outdoor applications, because articulated wheeled rovers offers both advantages of wheels and legs i.e. velocity for the first and obstacles crossing for the second. Their legs kinematics and compliance will be optimized for ensuring both reactive obstacle crossing and postural balance. High-level control will be also addressed by presenting recent advances in path planning and motion generation for mobile robots navigating autonomously over rough terrain. The main issue here is how we can obtain efficient prediction of rover stability and mobility for on-line path and motion planning.



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