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检索条件"机构=Bio Robotics Division Robotics Department Mechanical Engineering Laboratory"

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Cooperative sensing and adaptive behavior of parent-children type robot system in unstructured environment

Cooperative sensing and adaptive behavior of parent-children...

引用

Proceedings of the From Perception to Action Conference

作者： T. Shibata K. Ohkawa K. Tanie Bio Robotics Division Robotics Department Mechanical Engineering Laboratory Ministry of International Trade and Industry (MITI) Tsukuba Japan

This paper proposes a parent-children type robot system that moves in unstructured environments. The parent robot works as a leader of the system. The children robots work as sensors to sense their environments while touching them. The parent collects the sensory information of its environment and generates a map. In order to express the map effectively, this paper applies a structured neural network to memory. The neural network learns the sensory information incrementally. While using the network, the parent robot determines their behavior. On the other hand, the children are disposable. When some of the children malfunction because of their dangerous environment, the remaining children compensate for them and continue to work. Simulations are performed to show the effectiveness of the proposed system.

关键词： Robot sensing systems Intelligent robots Service robots Neural networks Control systems Intelligent control Intelligent structures mechanical engineering biosensors mechanical sensors

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Ecologically conscious automated disassembly system

Ecologically conscious automated disassembly system

引用

Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'94)

作者： T. Shibata K. Tanie Bio-Robotics Division Robotics Department Mechanical Engineering Laboratory M.I.T.I. Tsukuba Japan

Human beings are using and consuming resources to make various products. However, the resources on the earth are limited. Therefore, recycling of the resources is very important for human beings now and in the future. After use of the products, they are thrown away or burnt while discharging COx. The environment of the earth is being damaged and the resources are being exhausted. In order to reuse the resources and to protect the environment of the earth, this paper introduces a conceptual design of disassembly automation system for automated manufacturing with ecological recycling. The system employs many robots to disassemble the used products. The disassembly process has to deal with a lot of uncertainty of the used products, while assembly process does not have to deal with so much uncertainty of the products. This paper explains a configuration of the system, functions of the robots and some problems.< >

关键词： Earth Humans Recycling Manufacturing automation robotics and automation Uncertainty Protection Design automation Pulp manufacturing Robotic assembly

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Motion planning for a redundant manipulator by genetic algorithm

Motion planning for a redundant manipulator by genetic algor...

引用

International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： T. Abe T. Shibata K. Tanie M. Nose Komatsu Limited Japan Bio-Robotics Division Robotics Department Mechanical Engineering Laboratory M.I.T.I. Japan

A motion planning method is proposed for cutting a three dimensional workpiece by a redundant manipulator with six degrees of freedom. The method applies a genetic algorithm to optimize the rotational angles of the end-effector on a path. For a fitness function, an evaluation function is defined based on references from skilled operators. Using the proposed method the operator only has to determine a path without considering the redundant parameters. Simulations show the effectiveness of the proposed method.< >

关键词： Genetic algorithms Motion planning Optimization methods Manipulator dynamics Service robots Education Angular velocity Optimal control Redundancy Nose

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Fuzzy, neural network, and genetic algorithm based control system

Fuzzy, neural network, and genetic algorithm based control s...

引用

International Conference on Industrial Electronics, Control and Instrumentation

作者： T. Fukuda K. Shimojima T. Shibata Department of Mechano-Informatics and Systems University of Nagoya Nagoya Japan Bio-Robotics Division Robotics Department Mechanical Engineering Laboratory M.I.T.I. Tsukuba Japan

This paper introduces a hierarchical control scheme based on a fuzzy, neural network, and a genetic algorithm for intelligent robotics. The scheme has three levels: learning level, skill level and adaptation level. The learning level manipulates symbols to reason logically for control strategies. The skill level produces control references along with the control strategies and sensory information on environments. The adaptation level controls robots and machines while adapting to their environments which include uncertainties. For these levels and to connect them, artificial intelligence, neural networks, fuzzy logic, and genetic algorithms are applied to the hierarchical control system while integrating and synthesizing themselves. To be intelligent, the hierarchical control system learns various experiences both in top-down manner and bottom-up manner. The hierarchical control scheme is effective for intelligent robotics and mechatronics.< >

关键词： Fuzzy control Fuzzy neural networks Fuzzy systems Neural networks Genetic algorithms Control systems Intelligent robots Artificial intelligence Intelligent sensors Learning systems

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Automatic generation of hierarchical structure of fuzzy inference by genetic algorithm

Automatic generation of hierarchical structure of fuzzy infe...

引用

International Joint Conference on Neural Networks (IJCNN)

作者： H. Ishigami Y. Hasegawa T. Fukuda T. Shibata Shin-Nagoya Thermal Power Station Cyubu Electric Power Company Inc. Nagoya Japan Department of Mechano-Informatics and Systems University of Nagoya Nagoya Japan Bio-Robotics Division Robotics Department MITI Mechanical Engineering Laboratory Tsukuba Japan

This paper deals with an automatic generation algorithm of a hierarchical fuzzy inference using genetic algorithms and the delta rule. The fuzzy inference can be applied to various problems. However, the determination of the membership functions is a difficult problem because the determination depends on human experts. The auto-tuning methods of the fuzzy model have been proposed to develop the time-consuming operation used by human experts. The problem is that a number of the fuzzy rules in the multiple input and multiple output is needed in the case of simple fuzzy inference. Therefore, the authors propose an auto-tuning method of hierarchical fuzzy inference. The proposed method enables the fuzzy model to construct the optimal and the minimal structures. In this paper, the authors show the effectiveness of the proposed method by simulation of water tanks level control. This general system can be applied to robotic motion control, sensing and recognition problems.< >

关键词： Genetic algorithms Humans Fuzzy systems Control systems Power generation Robot motion Motion control Robot control Fuzzy neural networks Inference algorithms

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Conceptual design of disassembly automation system for automated manufacturing with ecological recycling

Conceptual design of disassembly automation system for autom...

引用

1993 IEEE/Tsukuba International Workshop on Advanced robotics: Can Robots Contribute to Preventing Environmental Deterioration?, ICAR 1993

作者： Shibata, Takanori Tanie, Kazuo Bio-Robotics Division Robotics Department Mechanical Engineering Laboratory MITI 1-2 Namiki Tsukuba305 Japan

ISBN: (纸本)0780314417

Human beings are using and consuming resources to make various products. However, the resources on the earth are limited. Therefore, recycling of the resources is very important for human beings now and in the future. After use of the products, they are thrown or burnt while discharging COx. The environment of the earth is being damaged and the resources are being exhausted. In order to reuse the resources and to protect the environment of the earth, this paper introduces a conceptual design of disassembly automation system for automated manufacturing with ecological recycling. The system employs many robots to disassemble the used products. The disassembly process has to deal with a lot of uncertainty of the used products, while assembly process does not have to deal with so much uncertainty of the products. This paper explains a configuration of the system, functions of the robots and some problems. © 1993 IEEE.

关键词： Conceptual design

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Learning scheme for recurrent neural network by genetic algorithm

Learning scheme for recurrent neural network by genetic algo...

引用

Proceedings of 1993 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '93)

作者： T. Fukuda T. Kohno T. Shibata Department of Mechano-Informatics and Systems University of Nagoya Nagoya Japan Bio Robotics Division Robotics Department Mechanical Engineering Laboratory Mechanical Engineering Laboratory Tsukuba Japan

Recurrent neural networks have dynamic characteristics and can express functions which depend on time. To apply these neural networks to the memory of robotic motions, i.e., trajectories of manipulators, it is necessary to determine appropriate network interconnection weights. A new learning scheme for recurrent neural networks using a genetic algorithm (GA) is presented and used to determine the interconnection weights. The GA approach is compared with backpropagation through time. Simulations illustrate the performance of the new approach.

关键词： Recurrent neural networks Genetic algorithms Neurons Neural networks Multi-layer neural network Cost function Electronic mail Feedforward neural networks International trade mechanical engineering

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Coordinative behavior in evolutionary multi-agent-robot system

Coordinative behavior in evolutionary multi-agent-robot syst...

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IEEE International Workshop on Intelligent Robots and Systems (IROS)

作者： T. Shibata T. Fukuda Bio Robotics Division Robotics Department Mechanical Engineering Laboratory Mechanical Engineering Laboratory Tsukuba Japan Department of Mechano-Informatics and Systems University of Nagoya Nagoya Japan

A new strategy for motion planning of multiple robots as a multi-agent system is proposed. The system has a decentralized configuration. All the robots cannot communicate globally, but some robots can communicate locally and coordinate to avoid conflicts for public resources. In such systems, it is difficult for each robot to plan its motion effectively while considering other robots, because the robots cannot predict the motion of other robots as an unknown environment. Therefore, each robot only determines its motion selfishly while considering a known environment. In the proposed approach, each robot plans its motion while considering the known environment and using empirical knowledge. The robot considers its unknown environment including the other robots in the empirical knowledge. A genetic algorithm is applied to optimize the planning of the motion of each robot. Through iterations, each robot acquires knowledge empirically using fuzzy logic For an illustration, this paper deals with path planning of multiple mobile robots and performs simulations.

关键词： Robot kinematics Humans Motion planning Intelligent control Multiagent systems mechanical engineering Laboratories International trade Strategic planning Fuzzy logic

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An image recognition method for rusty and damaged car parts after road traffic accident

An image recognition method for rusty and damaged car parts ...

引用

1993 IEEE/Tsukuba International Workshop on Advanced robotics: Can Robots Contribute to Preventing Environmental Deterioration?, ICAR 1993

作者： Ho, Kenneth H. L. Yamaba, Kazuo Autonomous Machinery Division Robotics Department Mechanical Engineering Laboratory AIST MITI Namiki 1-2 Tsukuba Ibaraki Pref.305 Japan

ISBN: (纸本)0780314417

This paper presents a new image recognition method. It tries to recognise undamaged car parts of a car after a road traffic accident. This Image recognition method defines concepts by using a set of images as examples. It will try to recognise a new image by collecting evidence from the images in the example set. A simple example was used to illustrate this method. © 1993 IEEE.

关键词： Image recognition

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Synthesis of fuzzy, artificial intelligence, neural networks, and genetic algorithm for hierarchical intelligent control-top-down and bottom-up hybrid method

Synthesis of fuzzy, artificial intelligence, neural networks...

引用

International Joint Conference on Neural Networks (IJCNN)

作者： T. Shibata T. Fukuda K. Tanie Bio-Robotics Division Robotics Department Mechanical Engineering Laboratory Tsukuba Japan Department of Mechano-Informatics and Systems University of Nagoya Nagoya Japan

Autonomous robots, which perform tasks without human operators, are required in many fields. They have to be intelligent to determine their own actions in unknown environments by themselves based on sensory information. In advance, human operators can give the robots knowledge and skill in top-down manner, but when the robots perform tasks in unknown environment, the knowledge may not be useful, In this case, the robots have to adapt to their environments and acquire new knowledge by themselves through learning. This process proceeds in bottom-up manner. This paper introduces a control scheme for autonomous robots, hierarchical intelligent control. It consists of three levels: adaptation level, skill level and learning level. To link the three levels, the scheme uses artificial intelligence (AI), fuzzy logic, neural networks (NN) and genetic algorithm (GA). Each technique has advantages and disadvantages. In order to overcome the disadvantages, this paper introduces synthesis techniques of them. Those are key techniques for intelligent control of robots. This paper describes advantages and disadvantages of each technique, and explains how to construct the hierarchical intelligent control.

关键词： Artificial intelligence Network synthesis Fuzzy control Fuzzy neural networks Artificial neural networks Genetic algorithms Intelligent networks Intelligent robots Robot sensing systems Intelligent control

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