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International Conference on Industrial Electronics, Control and Instrumentation

作者： T. Fukuda 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 for intelligent robotics and mechatronics. 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： Intelligent robots Control systems Intelligent systems Intelligent control Intelligent sensors Robot sensing systems Artificial intelligence Learning systems Mechatronics Control system synthesis

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Auto fuzzy tuning having minimum structure by using genetic algorithm and delta rule 2

Auto fuzzy tuning having minimum structure by using genetic ...

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2nd IEEE International Workshop on Emerging Technologies and Factory Automation: Design and Operations of Intelligent Factories, ETFA 1993

作者： Fukuda, T. Ishigami, H. Shibata, T. Arai, F. Nagoya University Department of Mechano-Informatics and Systems Furo-cho Chikusa-ku Nagoya464-01 Japan Cyubu Electric Power Co. Inc. Shin-Nagoya Thermal Power Station 34 Shiomi-cho Minato-ku Nagoya455 Japan Mechanical Engineering Laboratory Bio-Robotics Division Robotics Department MITI 1-2 Namiki Tsukuba305 Japan

ISBN: (纸本)0780309855

An auto tuning algorithm of fuzzy inference for Fuzzy neural networks using the genetic algorithm and the delta rule is presented. Some auto-tuning methods are proposed to reduce time-consuming operations by human experts. This tuning method brings the minimal and optimal structure of the fuzzy model. Two types of the fuzzy model are prepared, whose membership functions on the antecedent part consist of triangular and Gaussian type, respectively. The effectiveness of the proposed methods compared with the former methods is shown by simulation. The proposed method has the potential to be applied to robotic motion control, sensing and recognition problems. © 1993 IEEE.

关键词： Genetic algorithms

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Fuzzy Critic for intelligent planning by genetic algorithm

Fuzzy Critic for intelligent planning by genetic algorithm

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International Conference on Emerging Technologies and Factory Automation (ETFA)

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

A new strategy for motion planning is proposed. The strategy applies a genetic algorithm (GA) to optimize the motion planning. To evaluate the planned motion, the strategy also applies fuzzy logic to a fitness function. The fitness function is referred to as Fuzzy Critic. The Fuzzy Critic evaluates plans as populations in the GA with respect to multiple factors. Depending on the goals of the tasks, human operators can easily determine inference rules in the Fuzzy Critic because of the fuzzy logic. The strategy determines a path for a mobile robot which moves from a starting point to a goal point, while avoiding obstacles in a work space and picking up loads on the way. Simulation illustrates the effectiveness of the proposed strategy.< >

关键词： Genetic algorithms Motion planning Intelligent robots Fuzzy logic Humans Orbital robotics Strategic planning Robot kinematics Neural networks Mobile robots

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Auto fuzzy tuning having minimum structure by using genetic algorithm and delta rule

Auto fuzzy tuning having minimum structure by using genetic ...

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International Conference on Emerging Technologies and Factory Automation (ETFA)

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

关键词： Genetic algorithms Humans Fuzzy systems Convergence Fuzzy neural networks Control systems Optimization methods Thermal engineering Power generation Mechanical engineering

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Dynamic memory by recurrent neural network and its learning by genetic algorithm

Dynamic memory by recurrent neural network and its learning ...

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IEEE Conference on Decision and Control

作者： T. Fukuda T. Kohno T. Shibata Department of Mechano-Informatics and Systems University of Nagoya Nagoya Japan Dept. of Mechano-Inform. & Syst. Nagoya Univ. Japan Bio-Robotics Division Robotics Department Mechanical Engineering Laboratory M.I.T.I. Tsukuba Japan

Recurrent neural networks have dynamic characteristics and can express functions of time. The recurrent neural networks can be applied to memorize robotic motions, i.e. trajectory of a manipulator. For this purpose, it is necessary to determine appropriate interconnection weights of the network. Formerly, learning algorithms based on gradient search techniques have been shown. However, it is difficult for the recurrent neural network to learn such functions while using previous approaches because of much computing requirement and limitation of memory. This paper presents a new learning scheme for the recurrent neural networks by genetic algorithm (GA). The GA is applied to determine interconnection weights of the recurrent neural networks. The GA approach is compared with the backpropagation through time which is a famous learning algorithm for the recurrent neural networks. Simulations illustrate the performance of the proposed approach.< >

关键词： Recurrent neural networks Genetic algorithms Neural networks Multi-layer neural network Neurons Feedforward neural networks Cost function Feedforward systems Robots Mechanical engineering

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A Force Control Method Using the Relative Motion between the Manipulator and a Workpiece

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IFAC Proceedings Volumes 1993年第2期26卷 461-464页

作者： K. Watanabe T. Fukuda S.G. Tzafestas Department of Mechanical Engineering Faculty of Science and Engineering Saga University Honjomachi-1 Saga 840 Japan Department of Mechano-Informatics and Systems Faculty of Engineering Nagoya University Furocho Nagoya 464-1 Japan Intelligent Robotics and Control Unit Computer Science Division National Technical University of Athens Zografou Athens 157 73 Greece

Control methods based on using the relative motion between the manipulator and the workpiece are described for controlling the force of a one-dimensional manipulator, in which it is assumed that there are no collisions between the manipulator and the workpiece and we use a computed force law which is similar to the computed torque law in the trajectory tracking problem of a manipulator. We consider two cases depending on whether the position and velocity of the workpiece (or end-effector) are available or not to calculate the computed force control. The effectiveness of the proposed control methods is illustrated by some computer simulations.

关键词： PID control contact motion force control robots manipulator servomechanisms

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engineering Multi-Agent systems 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： Danny Weyns Viviana Mascardi Alessandro Ricci

ISBN: (数字)9783030256937

ISBN: (纸本)9783030256920

This book constitutes the revised and selected papers from the 6th International Workshop on engineering Multi-Agent systems held in Stockholm, Sweden, in July 2018, in conjunction with AAMAS 2018. The 17 full papers presented in this volume were carefully reviewed and selected from 32 submissions. The book also contains a state-of-the-art paper that reflects on the role and potential of MAS engineering in a number of key facets. The papers are clustered around the following themes: programming agents and MAS, agent-oriented software engineering, formal analysis techniques, rational agents, modeling and simulation, frameworks and application domains.

关键词： Artificial Intelligence Software engineering/Programming and Operating systems Information systems Applications (incl. Internet)

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DNA Computing and Molecular Programming 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： Satoshi Murata Satoshi Kobayashi

ISBN: (数字)9783319112954

ISBN: (纸本)9783319112947

This book constitutes the refereed proceedings of the 20th International Conference on DNA Computing and Molecular Programming, DNA 20, held in Kyoto, Japan, in September 2014. The 10 full papers presented were carefully selected from 55 submissions. The papers are organized in many disciplines (including mathematics, computer science, physics, chemistry, material science and biology) to address the analysis, design, and synthesis of information-based molecular systems.

关键词： Computation by Abstract Devices Algorithm Analysis and Problem Complexity Computational Biology/Bioinformatics Artificial Intelligence Data Structures Discrete Mathematics in Computer Science

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Estimating Functional Connectivity and Topology in Large-Scale Neuronal Assemblies 1

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丛书名： Springer Theses

1000年

作者： Vito Paolo Pastore

ISBN: (数字)9783030590420

ISBN: (纸本)9783030590413;9783030590444

This book describes a set of novel statistical algorithms designed to infer functional connectivity of large-scale neural assemblies. The algorithms are developed with the aim of maximizing computational accuracy and efficiency, while faithfully reconstructing both the inhibitory and excitatory functional links. The book reports on statistical methods to compute the most significant functional connectivity graph, and shows how to use graph theory to extract the topological features of the computed network. A particular feature is that the methods used and extended at the purpose of this work are reported in a fairly completed, yet concise manner, together with the necessary mathematical fundamentals and explanations to understand their application. Furthermore, all these methods have been embedded in the user-friendly open source software named SpiCoDyn, which is also introduced here. All in all, this book provides researchers and graduate students in bioengineering, neurophysiology and computer science, with a set of simplified and reduced models for studying functional connectivity in in silico biological neuronal networks, thus overcoming the complexity of brain circuits.

关键词： Biomedical engineering and bioengineering Complexity Coding and Information Theory Graph Theory

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AIxIA 2021 – Advances in Artificial Intelligence 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： Stefania Bandini Francesca Gasparini Matteo Palmonari Giuseppe Vizzari Viviana Mascardi

ISBN: (数字)9783031084218

ISBN: (纸本)9783031084201

The 36 full papers included in this book were carefully reviewed and selected from 58 submissions; the volume also contains 12 extended and revised workshop contributions. The papers were organized in topical sections as follows: Planning and strategies; constraints, argumentation, and logic programming; knowledge representation, reasoning, and learning; natural language processing; AI for content and social media analysis; signal processing: images, videos and speech; machine learning for argumentation, explanation, and exploration; machine learning and applications; and AI applications.

关键词： Artificial Intelligence Information systems and Communication Service Computer Imaging, Vision, Pattern Recognition and Graphics Computer Applications

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