Neural Network-Based Learning Impedance Control for a Robot

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概要

• 論文の詳細を見る

• In this paper, a neural network-based learning approach for robot impedance control is presented to accomplish a contact task. Firstly, a discrete-time impedance control algorithm is obtained to control the contact task of the robot. Secondly, on-line learning algorithms based on a new evaluation function are developed for the neural networks which adjust the inertia, damping and stiffness parameters of the robot in order to adapt it to the unknown contact environment. Thirdly, experiments are carried out and the effecttiveness of the present approach is verified by pressing a spring using a 6 degrees of freedom robot. The adaptiveness, stability and flexibility of the present approach are also confirmed by the experimental results.

• 一般社団法人日本機械学会の論文
• 2001-09-15

著者

• Todo Isao

  Department Of Mechanical Engineering And Materials Science Yokohama National University

• XIAO NanFeng

  Department of Mechanical Engineering and Materials Science, Yokohama National University

• Xiao Nanfeng

  Department Of Mechanical Engineering And Materials Science Yokohama National University

関連論文

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• Neural Network-Based Learning Impedance Control for a Robot
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• Assembly Method of Blocks for Structures
• Cooperative Control of Two Direct-Drive Robots Using Neural Networks : Grasping and Movement of an Object

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