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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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Fuzzy clustering involving convex polytopes

Fuzzy clustering involving convex polytopes

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Il Hong Suh Jae-Hyun Kim F. Chung-Hoon Rhee Intelligent Control and Robotics Laboratory Department of Electronic Engineering Hanyang University Ansan South Korea

Prototype based methods are commonly used in cluster analysis and the results may be highly dependent on the prototype used. In this paper, we propose a fuzzy clustering method that involves adaptively expanding convex polytopes. Thus, the dependency on the use of prototypes can be eliminated. Also, the proposed method makes it possible to effectively represent an arbitrarily distributed data set without a priori knowledge of the number of clusters in the data set. Specifically, nonlinear membership functions are utilized to determine whether a new cluster is created or which vertex of the cluster should be expanded. For this, the membership function of a new vertex is assigned according to not only a distance measure between an incoming pattern vector and a current vertex, but also the amount of how much the current vertex has been modified. Therefore, cluster expansion can be only allowed for one cluster per incoming pattern. Several experimental results are given to show the validity of our method.

关键词： Prototypes Clustering algorithms Phase change materials Shape Amorphous materials Fuzzy neural networks intelligent control intelligent robots Laboratories Design engineering

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Design of a supervisory control system for multiple robotic systems

Design of a supervisory control system for multiple robotic ...

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IEEE International Workshop on intelligent Robots and Systems (IROS)

作者： I.H. Suh H.J. Yeo J.H. Kim J.S. Ryoo S.R. Oh C.W. Lee B.H. Lee Intelligent Control and Robotics Laboratory Department of Electronics Engineering Hanyang University Ansan Kyunggi South Korea Advanced Robotics Research Center KIST Seoul South Korea Department of Control and Instrumentation Engineering Seoul National University South Korea

This paper presents a design experience of a supervisory control system for coordination of multiple robotic devices. To effectively program job commands, a Petri net-type graphical robot language(PGRL) is proposed, where some functions for coordination among tasks such as concurrency and synchronization, can be easily programmed. Each task of PGRL is described by employing formal model languages, which are composed of three modules, sensory, data handling, and action module. It is expected that by using our proposed PGRL and formal model languages, one can efficiently describe a job or task, and hence can easily operate a complex real-time concurrent system. The proposed control system has been implemented by using VME-based 32-bit microprocessor boards and a real-time multitasking operating system (VxWorks), and is shown to successfully work for robotic jobs.

关键词： Supervisory control Robot kinematics Robot sensing systems Real time systems Concurrent computing Data handling control systems Microprocessors Multitasking Operating systems

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An intelligent coordinated control system for steering and traction of electric vehicles

An intelligent coordinated control system for steering and t...

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International Conference on Industrial Electronics, control and Instrumentation

作者： M.K. Park I.H. Suh S.J. Byoun S.R. Oh Intelligent Control and Robotics Laboratory Department of Electronics Engineering Hanyang University Seoul South Korea Department of Control and Instrumentation Engineering Dong Yang University Youngju South Korea Division of Electronics Information Technology India

An intelligent coordinated control system is designed for the active steering and the left/right traction force distribution control of 2-wheel-drive and 2-wheel-steering (2WD/2WS) electric vehicles, where input-output linearization is employed. Also, a fuzzy-rule-based cornering force estimator is suggested to avoid using an uncertain highly nonlinear expression, and a neural network compensator is additionally utilized for the estimator to correctly find cornering force. With these techniques, the proposed control system is shown by simulation results to be robust against drastic change of the external environments such as road conditions.

关键词： intelligent systems intelligent control control systems Force control intelligent vehicles Electric vehicles Neural networks control system synthesis Robust control Roads

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Commanding sensors and controlling indoor autonomous mobile robots

Commanding sensors and controlling indoor autonomous mobile ...

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IEEE Conference on control Technology and Applications (CCTA)

作者： M. Dekhil T.M. Sobh A.A. Efros Department of Computer Science University of Utah Salt Lake UT USA Robotics Intelligent Sensing imd Control Laboratory Department of Computer Science and Engineering University of Bridgeport Bridgeport CT USA

Any sensory system can be viewed as a passive or dumb element which provides raw data. It can also be viewed as an intelligent element which returns "analyzed" information. Finally, it can be viewed as a commanding element which sends commands to the physical system. Each of these views is used in different situations and for different tasks. Commanding sensors are an extension to the logical sensor approach in which a mapping from events to actions is added to the sensor model. In a previous paper (1995), we proposed a sensor-based distributed control scheme for mobile robots along with several simulation results. In this paper, the application of this scheme to control a real mobile robot is presented and the results of several experiments are discussed. A server-client model is used to implement this scheme where the server is a process that carries out the commands to be executed, and each client is a process with a certain task. The logical sensor approach is used to model the sensory system which provides different levels of data representation with tolerance measures and analysis.

关键词： Mobile robots intelligent sensors control systems Sensor systems Centralized control intelligent robots Computer science Delay Cities and towns Robot sensing systems

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Measuring the distance and orientation of a planar surface using nonstructured lighting

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SYSTEMS AND COMPUTERS IN JAPAN 1996年第8期27卷 83-92页

作者： Tsukiyama, T Member Electrotechnical Laboratory Tsukuba Japan 305 Tosbifumi Tsukiyama:graduated in 1972 from the Biological Engineering Department Osaka University where he also received his Dr. of Eng. degree. He joined Electrotechnical Laboratory Ministry of Tread and Industry (Japan) in 1972. At present he is Senior Researcher at Computer Vision Section Intelligent Systems Division ETL. He was a Visiting Researcher at University of Illinois during 1984–1985. He has been interested in vision system for mobile robots and image processing architectures. He is a member of the Society of Instrumental and Control Engineers Japan Robotics Society of Japan and Information Processing Society of Japan.

This paper proposes a method of 3-dimensional measurement of a planar surface by using two fixed light sources and a TV camera. A set of two images is recorded by the camera switching on each light alternately. The peak of the luminance distribution in each image is detected, and the orientation and distance of the planar surface are calculated. The position of the peak of a luminance distribution can be estimated accurately by using an image processing. The light sources can be conventional apparatus with no particular structure. The method is simple and suitable for a vision system on an indoor mobile robot.

关键词： distance to surface orientation of planar surface point light source luminance distribution ring light

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