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IEEE International Workshop on intelligent Robots and Systems (IROS)

作者： Y. Hayashibara T. Takubo Y. Sonoda H. Arai K. Tanie Department of Control and System Engineering Toin University of Yokohama Yokohama Kanagawa Japan System Electronics Tokyo Engineering University Hachioji Tokyo Japan Institute of Engineering Mechanics University of Tsukuba Tsukuba Ibaraki Japan Robotics Department Mechanical Engineering Laboratory AIST-MITI Tsukuba Ibaraki Japan

Deals with an assist system for carrying a long object with a human operator. When we carry such an object, we often grasp both ends and move it cooperatively. Our purpose is to establish how to design the assist system which can achieve such a task. It is difficult to apply conventional control laws. On the other hand, humans can achieve such a task. Therefore, we measure the human cooperative behaviors and analyze them to find the cooperative rules. Based on the rules, we propose a control law of the assist system. Furthermore, we construct a prototype system and verify the validity of the control law.

关键词： Humans control systems Anthropometry Force sensors Force measurement Computer displays Systems engineering and theory Prototypes Robot sensing systems Torque

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Dynamic process initial conditions in repetitive processes. controllability and stability analysis

Dynamic process initial conditions in repetitive processes. ...

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Information, Decision and control (IDC)

作者： K. Galkowski E. Rogers A. Gramacki J. Gramacki D.H. Owens Institute of Robotics and Software Engineering Technical University of Zielona Góra Zielona Gora Poland Department of Electronics and Computer Science Image Speech and Intelligent Systems Research Group University of Southampton Southampton UK Institute of Computer Engineering and Electronics Technical University of Zielona Góra Zielona Gora Poland School of Engineering Centre for Systems and Control Engineering University of Exeter Exeter UK

Repetitive, or multipass, processes are a class of 2D systems of both practical and algorithmic/theoretical interest whose dynamics cannot be analysed or controlled using standard (1D) systems theory. Recently it has been shown that the modelling of the boundary conditions, also known as the process initial conditions, is a crucial feature in the analysis and control of these processes. This paper presents some further results on the effects of so-called 'dynamic' process initial conditions on the controllability and stability properties of discrete linear repetitive processes. Previous work has shown that these dynamic process initial conditions alone can destroy the stability properties of these processes. Hence their effects must be 'adequately' accounted for the process modelling stage in order to ensure that subsequent analysis does not lead to incorrect results/conclusions. The main results developed in this paper can be summarised as follows. (i) Computationally efficient stability tests which can, in effect, be applied using standard, or 1D, linear systems tests. (ii) Characterisation of so-called pass controllability in the form of matrix rank based conditions. (iii) Conditions under which the dynamic process initial conditions can be selected to ensure stability and pass controllability.

关键词： Stability controllability System testing control system analysis Algorithm design and analysis control systems Boundary conditions Process control Standards development Linear systems

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Robotic assistants for aircraft inspectors

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IEEE Instrumentation and Measurement Magazine 1998年第1期1卷 16-30页

作者： Siegel, Mel Gunatilake, Priyan Podnar, Gregg Intelligent Sensor Msrmt. C. Robotics Institute Carnegie Mellon University University of Colorado JILA University of Virginia SUNY Buffalo NY United States Extranuclear Laboratories ABB-Extrel Aircraft Diagnostics Corporation University of Alaska Fairbanks AK United States Elec. and Comp. Eng. Department Carnegie Mellon University CMU Vis. Lab. of the Robotics Institute CMU Mobile Robot Laboratory Engineering Design Research Center CMU Computer Science Department JiangXi University Robotics Institute Measurement and Control Laboratory

Various alternative aircraft inspection methods are first discussed and advantages of using robots are analysed. ANDI (Automated NonDestructive Inspector) and CIMP (Crown Inspection Mobile Platform) are then described. Remote 3D stereoscopic visual inspection is outlined and algorithms developed for crack detection and surface and subsurface corrosion detection are described. Future development trends are also outlined.

关键词： Robots Aircraft Aerospace electronics Instruments

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Region-based Q-learning for intelligent robot systems

Region-based Q-learning for intelligent robot systems

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IEEE International Symposium on Computational Intelligence in robotics and Automation (CIRA)

作者： I.H. Suh J.H. Kim S.R. Oh Intelligent Control and Robotics Laboratory Department of Electronics Eng Hanyang University Kyunggi South Korea

It is desirable for autonomous robot systems to possess the ability to behave in a smooth and continuous fashion when interacting with an unknown environment. Since Q-learning requires a lot of memory and time to optimize a series of actions in a continuous state space, it may not be easy to apply the method to such a real environment. In this paper, for a continuous state space application, we propose a new method of Q-learning that incorporates a region-based reward assignment being used to solve a structural credit assignment problem and a triangular type Q-value model. Our learning method can estimate a current Q-value by a relationship with its neighboring states and has the ability to learn its actions similar to that of Q-learning. Thus, our method can enable robots to move smoothly in a real environment. To show the validity of our method, navigation comparison with Q-learning is given and visual tracking simulation results involving a 2-DOF SCARA robot are also presented.

关键词： intelligent robots State-space methods Learning systems Navigation intelligent control Orbital robotics Optimization methods State estimation control systems Fuzzy sets

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Artificial immune network-based cooperative control in collective autonomous mobile robots

Artificial immune network-based cooperative control in colle...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Dong-Wook Lee Kwee-Bo Sim Robotics and Intelligent Information System Laboratory Department of Control and Instrumentation Engineering Chung Ang University Seoul South Korea

In this paper, we propose a method of cooperative control based on immune system in distributed autonomous robotic system (DARS). Immune system is living body's self-protection and self-maintenance system. Thus these features can be applied to decision making of optimal swarm behavior in dynamically changing environment. For the purpose of applying the immune system to DARS, a robot is regarded as a B lymphocyte (B cell), each environmental condition as an antigen and a behavior strategy as an antibody respectively. The executing process of proposed method is as follows: when the environmental condition changes, a robot selects an appropriate behavior strategy, and its behavior strategy is stimulated and suppressed by other robot using communication. Finally, such stimulated strategy is adopted as a swarm behavior strategy. This control scheme is based on clonal selection and idiotopic network hypothesis, and it is used for decision making of an optimal swarm strategy.

关键词： intelligent networks Mobile robots Immune system control systems intelligent robots Mobile communication Decision making Humans Robot sensing systems intelligent systems

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Behavior learning and evolution of collective autonomous mobile robots based on reinforcement learning and distributed genetic algorithms

Behavior learning and evolution of collective autonomous mob...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Hyo-Byung Jun Kwee-Bo Sim Robotics and Intelligent Information System Laboratory Department of Control and Instrumentation Engineering Chung Ang University Seoul South Korea

In this paper, we present the reinforcement learning and distributed genetic algorithm based behavior learning of the distributed autonomous mobile robots. The internal reinforcement signal for the reinforcement learning is generated by fuzzy inference, and dynamic recurrent neural networks are used as action generation module. We adopt the distributed genetic algorithms for the cooperative behavior emergence. We show the validity of the proposed learning and evolution algorithm by computer simulation.

关键词： Mobile robots Learning Genetic algorithms Inference algorithms Signal generators intelligent robots Animals Mobile communication Education intelligent systems

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Fuzzy-Q learning for autonomous robot systems

Fuzzy-Q learning for autonomous robot systems

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International Conference on Neural Networks

作者： Il Hong Suh Jae-Hyun Kim F.C.-H. Rhee Intelligent Control and Robotics Laboratory Department of Electronic Engineering Hanyang University Ansan South Korea Computational Vision and Fuzzy Systems Laboratory Hanyang University Ansan South Korea

It is desirable for autonomous robot systems to posses the ability to behave in a smooth and continuous fashion when interacting with an unknown environment. Since Q-learning is normally used for optimizing a series of discrete actions, it may be undesirable when applied to a real environment which involves continuous states and actions. In this paper, we propose a new method of Q-learning that incorporates a fuzzy interpolation technique which is used to approximate a continuous state. Our learning method can estimate current state by its neighboring states and has the ability to learn its actions similar to that of Q-learning. Thus, our method can enable robots to react smoothly in a real environment. Simulation results involving an autonomous robot are given to show the validity of our method.

关键词： Robot sensing systems control systems Laboratories Interpolation State estimation intelligent robots Learning Robot control Robot vision systems Machine vision

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Region-based Q-learning using convex clustering approach

Region-based Q-learning using convex clustering approach

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IEEE International Workshop on intelligent Robots and Systems (IROS)

作者： J.H. Kim I.H. Suh S.R. Oh Y.J. Cho Y.K. Chung Intelligent Control and Robotics Laboratory Department of Electronics Engineering Hanyang University Ansan Kyunggi South Korea Advanced Robotics Research Center KIST Seoul South Korea School of Mechanical Engineering Information Research Laboratories PIRL Pohang University of Science and Technology South Korea

For continuous state space applications, a novel method of Q-learning is proposed, where the method incorporates a region-based reward assignment being used to solve a structural credit assignment problem and a convex clustering approach to find a region with the same reward attribution property. Our learning method can estimate a current Q-value of an arbitrarily given state by using effect functions, and has the ability to learn its actions similar to that of Q-learning. Thus, our method enables robots to move smoothly in a real environment. To show the validity of our method, the proposed Q-learning method is compared with conventional Q-learning method through a simple two dimensional free space navigation problem, and visual tracking simulation results involving a 2-DOF SCARA robot are also presented.

关键词： Orbital robotics Learning systems intelligent robots State-space methods Mechanical engineering Mechanical factors State estimation Motion planning Discrete event simulation Humans

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Geometric collision detection and potential field based time delay planning for dual arm systems

Geometric collision detection and potential field based time...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Sukhan Lee H. Moradi G. Kardaras Sung-Kwon Kim Jet Propulsion Laboratory California Institute of Technology Pasadena CA USA Department of Computer Science-EE Systems Institute for Robotics and Intelligent Systems University of Southern California Los Angeles CA USA Production Engineering Center Samsung Electronics Company Limited Suwan South Korea

In this paper a method for collision detection and collision avoidance for dual arm robots is proposed. The collision detection, a fast geometric approach based on link intersection, detects the collision and constructs the collision region for given trajectories. The time delay planning determines the minimum necessary time delay to avoid collisions using a potential field representation for collision regions. The planning is based on a flexible, massively parallel approach. It effectively avoids any local minima problems due to the potential field representation and can be used regardless of the complexity of the collision region (e.g., concave or complicated regions).

关键词： Delay effects Robotic assembly Manipulators Orbital robotics intelligent robots Parallel robots Parallel processing Assembly systems robotics and automation Path planning

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A simple adaptive scheme for indirect field orientation of an induction motor

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EUROPEAN TRANSACTIONS ON ELECTRICAL POWER 1997年第4期7卷 243-249页

作者： Branco, PJC [?]Paulo Jose da Costa Branco (1965) received the B.Sc. and M.Sc. degrees in Electrical Engineering from the Universidade Federal do Rio de Janeiro (UFRJ) Rio de Janeiro/Bnsil in 1988 and 1991 respectively. Since 1992 he has been an Assistant at the Department of Electrical and Computing Engineering Section of Electrical Machines and Power Electronics in the Instituto Superior Tecnico (I.S.T.). He is currently working toward the Ph.D. degree in Electrical Engineering in an application of fuzzy learning theory in the design of “intelligent” electromechanica1 systems. His majorfieldsof interest are Control of Electrical Drives mainly their rncdellization and control using fuzzy logic and neural networks energy conservation and non-linear dynamic systems. In April I992 he joined at Centro de Automictica of Universidade Tecnica de Lisboa (CAUTL) as a researchassistant and in 1993 joined to the Mechatronics Laboratory in the same university. (Instituto Superior TCcnico (I.S.T.) Department of Electrical and Computing Engineering. Section of Electrical Machines and Power Electronics Lisboflortugal Phone: +35 I 1/8417432 Fax: +3511/848 29 87 E-mail: pbranco@alfa.ist.utl.pt)

A self-adaptive scheme is described for automatically tracking the temperature and saturation-dependent rotor time constant T-r in indirect vector control. This method is based on a monitoring signal injected into the process. A cross-correlation function between the monitoring signal and the speed error indicates the T-r changes in direction (increase or decrease) and magnitude. The proposed identification algorithm presents unique characteristics: it does not use current or voltage sensors;it is not motor-parameter dependent;the amplitude of the monitoring signal can be reduced but with an increase on the speed-error sensibility to control interference in drive's performance and it works either on steady-and dynamic transient-state. it will need some load to operate but this condition is satisfied in all practical cases. Tests were conducted with a 1.2 kW four-quadrant AC drive. The adaptive indirect vector-control was implemented in a microcomputer with the motor supplied by a voltage-source inverter with current control using IGBT Experimental and simulated results using this adaptive digital scheme for different loads and values of model T-r(representing a detuned operation) are presented showing good performances.

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