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IEEE/RAS-EMBS International Conference on Biomedical robotics and Biomechatronics (BioRob)

作者： John N. Karigiannis Costas S. Tzafestas Faculty of Electrical and Computer Engineering Division of Signals Control and Robotics National and Technical University of Athens Athens Greece

In the context of multi-agent systems, we are proposing a hierarchical robot control architecture that comprises artificial intelligence (AI) techniques and traditional control methodologies, based on the realization of a learning team of agents in a continuous problem setting. In a multi-agent system, action selection is important for cooperation and coordination among the agents. By employing reinforcement learning (RL) methods in a fuzzified state-space, we accomplish to design a control architecture and a corresponding methodology, engaged in a continuous space, which enables the agents to learn, over a period of time, to perform sequences of continuous actions in a cooperative manner, in order to reach their goal without any prior generated task model. By organizing the agents in a nested architecture, as proposed in this work, a type of problem-specific recursive knowledge acquisition is attempted. Furthermore, the agents try to exploit the knowledge gathered in order to be in position to execute tasks that indicate certain degree of similarity. The agents correspond in fact to independent degrees of freedom of the system, and achieve to gain experience over the task that they collaboratively perform, by exploring and exploiting their state-to-action mapping space. A numerical experiment is presented in this paper, performed on a simulated planar 4 degrees of freedom (DOF) manipulator, in order to evaluate both the proposed hierarchical multi-agent architecture as well as the proposed methodological framework. It is anticipated that such an approach can be highly scalable for the control of robotic systems that are kinematically more complex, comprising multiple DOFs and potentially redundancies in open or closed kinematic chains, particularly dexterous manipulators.

关键词： Kinematics State-space methods Learning Multiagent systems Robot control Artificial intelligence control systems Manipulators Organizing Knowledge acquisition

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IEEE Transactions on Haptics: Editorial

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IEEE Transactions on Haptics 2008年第1期1卷 2-8页

作者： Edward Colgate, J. Lederman, Susan Prattichizzo, Domenico Barbagli, Federico Basdogan, Cagatay Buss, Martin Ernst, Marc Frisoli, Antonio Gillespie, Brent Grant, Danny Harders, Matthias Hayward, Vincent Jones, Lynette Kajimoto, Hiroyuki Kappers, Astrid Kheddar, Abderrahmane Lin, Ming C. MacLean, Karon Miller, Brian Noma, Haruo Okamura, Allison M. O'Malley, Mareia Ryu, Jeha Tan, Hong Z. Yokokohji, Yasuyoshi Department of Psychology School of Computing Queen's University Canada IEEE Robotics and Automation Society Tübingen Germany Stanford University's Computer Science Department Tübingen Germany Institute of Automatic Control Engineering Technische Universität München Germany Independent Research Group Multisensory Perception and Action Max Planck Institute for Biological Cybernetics Tübingen Germany Department of Applied Mechanics SSSA Japan Research Division Virtual Reality and Telerobotic Systems PERCRO Laboratory Japan Department of Mechanical Engineering Japan Department of Robotics McGill University Canada Computer Vision Lab ETH Zurich Japan Virtual Reality in Medicine Group Japan IEEE CS/RAS Technical Committee on Haptics Japan Department of Electrical and Computer Engineering McGill University Canada Department of Mechanical Engineering MIT Japan University of Electro-Communications Japan Department of Physics and Astronomy Utrecht University Netherlands University of Evry France Chapel Hill United States Department of Computer Science University of British Columbia Canada ATR Knowledge Science Lab United Kingdom Department of Mechanical Engineering Denmark Johns Hopkins University United States Laboratory for Computational Sensing and Robotics United Kingdom Engineering Research Center for Computer-Integrated Surgical Systems and Technology United States Mechanical Engineering and Materials Science Department Rice University United States Korea Republic of Department of Electrical and Computer Engineering Mechanical Engineering and Psychological Sciences Purdue University United States Department of Mechanical Engineering and Science Graduate School of Engineering Kyoto University Japan

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Erratum to “Delay-independent absolute stability for time-delay Lur'e systems with sector and slope restricted nonlinearities” [Phys. Lett. A 372 (2008) 4010]

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Physics Letters A 2009年第22期373卷 1997-1997页

作者： S.M. Lee O.M. Kwon Ju H. Park Platform Verification Division BcN Business Unit KT Co. Ltd. Daejeon Republic of Korea School of Electrical & Computer Engineering 12 Gaeshin-Dong Heungduk-Gu Chungbuk National University Cheongju Republic of Korea Robust Control and Nonlinear Dynamics Laboratory Department of Electrical Engineering Yeungnam University 214-1 Dae-Dong Kyongsan 712-749 Republic of Korea

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A CMAC-Q-Learning based Dyna agent

A CMAC-Q-Learning based Dyna agent

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SICE Annual Conference

作者： Yuan-Pao Hsu Wei-Cheng Jiang Hsin-Yi Lin Department of Computer Science and Information Engineering National Formosa University Yunlin Taiwan Robotics Control Technology Department Intelligent Robotics Technology Division Industrial Technology and Research Institute Hsinchu Taiwan

In the this paper, a CMAC-Q-learning based Dyna agent is presented to relieve the problem of learning speed in reinforcement learning, in order to achieve the goals of shortening training process and increasing the learning, speed. We combine CMAC, Q-learning, and prioritized sweeping techniques to construct the Dyna agent in which a Q-learning is trained for policy learning; meanwhile, model approximators, called CMAC-model and CMAC-R-model, are in charge of approximating the environment model. The approximated model provides the Q-learning with virtual interaction experience to further update the policy within the time gap when there is no interplay between the agent and the real environment. The Dyna agent switches seamlessly between the real environment and the virtual environment model for the objective of policy learning. A simulation for controlling a differential-drive mobile robot has been conducted to demonstrate that the proposed method can preliminarily achieve the design goal.

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Adaptive impedance control in haptic teleoperation to improve transparency under time-delay

Adaptive impedance control in haptic teleoperation to improv...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Costas Tzafestas Spyros Velanas George Fakiridis School of Electrical and Computer Engineering Division of Signals Control and Robotics National and Technical University of Athens Greece National Technical University of Athens Athens GR

This paper proposes the application of an adaptive impedance control scheme to alleviate some of the problems associated with the presence of time delays in a haptic teleoperation system. Continuous on-line estimation of the remote environment's impedance is performed, and is then used as a local model for haptic display control. Lyapunov stability of the proposed impedance adaptation law is demonstrated. A series of experiments is performed to evaluate the performance of this teleoperation control scheme. Two performance measures are defined to assess transparency and stability of the teleoperator. Simulation results show the superior performance of the proposed adaptive scheme, with respect to direct teleoperation, particularly in terms of increasing the stability margin and of significantly ameliorating transparency in the presence of large time delays. Experimental results, using a phantom omni as the haptic master device, support this conclusion.

关键词： Programmable control Adaptive control Impedance Haptic interfaces Delay effects Stability control systems Displays Lyapunov method Performance evaluation

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Robust adaptive control of a twin-roaor Aircraft

Robust adaptive control of a twin-roaor Aircraft

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IEEE Conference on Decision and control

作者： P. Krishnamurthy F. Khorrami Q. Lam IntelliTech MicroSystems Inc. Bowie MD USA Control/Robotics Research Laboratory (CRRL) Department of Electrical and Computer Engineering Polytechnic University Brooklyn NY USA Orbital Sciences Corporation Dalles VA USA

We propose robust adaptive control designs for a twin-rotor aircraft with specific focus on attaining good disturbance attenuation properties to facilitate operation in a shipboard environment wherein the aircraft is subject to severe aerodynamic disturbances including ship airwake, deck vortices, and rotor downwash especially during ship roll and pitch motions. Furthermore, the controllers can operate on their own or can gracefully co-exist with a baseline controller in a control augmentation fashion thus minimizing flight software change impact. The performance of the proposed controllers was validated through extensive simulation studies.

关键词： Robust control Adaptive control Aircraft Aerospace control Aerodynamics Marine vehicles Three-term control Error correction Motion control Attenuation

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Motivation and Competitive Learning in a Social Robot

Motivation and Competitive Learning in a Social Robot

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2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, Pages 3661-4172

作者： Salvador Dominguez Eduardo Zalama Jaime G. Garcia-Bermejo Jaime Pulido Robotics Computer Vision and Real Time Division CARTIF Foundation Boecillo Valladolid Spain DepDepartment of Systems Engineering and Automatic Control Industrial Engineering School University of Valladolid Spain University of Valladolid (Spain) Dep. of Systems Engineering and Automatic Control Industrial Engineering School Comput. Vision & Real Time Div. CARTIF Found. Valladolid

ISBN: (纸本)9781424420575

This paper describes the motivation and learning subsystems of Arisco which is a mechatronic head with interactive capacity which includes high expressivity through gesturing, voice recognition, text to speech generation, visual tracking, and internet information retrieval. The general architecture is first described in the paper. Then, the learning capacity of Arisco is addressed. It learns and performs associations between different stimulus responses through several dynamic neural networks, guided by motivational drives. A number of experiments are discussed, covering stimulus competition, habituation, classical and operant conditioning.

关键词： Social robot learning interaction computer vision motivation

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Temporal Occupancy Grid for mobile robot dynamic environment mapping

Temporal Occupancy Grid for mobile robot dynamic environment...

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2007 Mediterranean Conference on control and Automation, MED

作者： Mitsou, Nikos C. Tzafestas, Costas S. School of Electrical and Computer Engineering Division of Signal Control and Robotics National Technical Univ. of Athens Athens 15773 Greece

ISBN: (纸本)142441282X

Mapping dynamic environments is an open issue in the field of robotics. In this paper, we extend the well known Occupancy Grid structure to address the problem of generating valid maps for dynamic indoor environments. We propose a spatiotemporal access method to store all sensor values (instead of preserving only one value for each cell as in the common occupancy grid case). By searching for similar time series, we can detect moving objects that appear only in a limited number of possible configurations (e.g. doors or chairs). Simulated experiments demonstrate the potentialities of the proposed system. ©2007 IEEE.

关键词： Mapping

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Output feedback decoupling of neutral time delay systems

Output feedback decoupling of neutral time delay systems

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2007 Mediterranean Conference on control and Automation, MED

作者： Panagiotakis, G.E. Koumboulis, F.N. Paraskevopoulos, P.N. Halkis Institute of Technology Department of Automation 34400 Psahna Evias Greece National Technical University of Athens Division of Signals Control and Robotics Department of Electrical and Computer Engineering 15773 Zographou Athens Greece

ISBN: (纸本)142441282X

The problem of Input Output Decoupling is studied for the case of general neutral multi-delay systems, via proportional realizable output feedback. Using a pure algebraic approach, the necessary and sufficient conditions for the problem to have a realizable solution are established and the general analytical expressions of the proportional realizable controller matrices, are derived. © 2007 IEEE.

关键词： Timing circuits

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Model matching of SISO neutral time delay systems via output feedback

Model matching of SISO neutral time delay systems via output...

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2007 Mediterranean Conference on control and Automation, MED

作者： Koumboulis, F.N. Kouvakas, N.D. Paraskevopoulos, P.N. Halkis Institute of Technology Department of Automation 34400 Psahna Evias Halkis Greece National Technical University of Athens Division of Signals Control and Robotics Department of Electrical and Computer Engineering 15773 Zographou Athens Greece

ISBN: (纸本)142441282X

The necessary and sufficient conditions for the solvability of the exact model matching problem for general neutral single input - single output multi-delay systems, via a realizable dynamic output feedback and a realizable dynamic precompensator, are established. The general class of the realizable dynamic controllers solving the problem is analytically determined. The results are successfully applied to the model of a cascade connection of two mixers as well as a numerical example. ©2007 IEEE.

关键词： Timing circuits

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