神経回路により出力誤差のフィードバックを行う逆運動学問題の解法

神経回路により出力誤差のフィードバックを行う逆運動学問題の解法利用統計を見る

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アイテムタイプ	学術雑誌論文 / Journal Article
言語	日本語
キーワード	Inverse-kinematics, Neural Networks, Output Feedback Inverse Model, Linear Adaptive System
その他のタイトル	Methods for Solving Inverse-kinematics Problems Using Nerual Networks with 0utput Error Feedback
著者	大山英明舘暲
著者別名	Oyama Eimei Tachi Susumu
著者所属	工業技術院機械技術研究所東京大学工学部
抄録	Many studies on the learning control of the robot arm have been conducted by using neural networks, The method that uses an acquired inverse-kinematics model of the arm by learning are popular. However, acquisition of the inverse-kinematics model has a number of drawbacks. Furthermore, a limited scale neural networks system has only limited precision. Errors still remains in the output of the inverse-kinematics model using the neural networks system. In this paper, a new method for solving inverse-kinematics problem using the learned inverse model of the linearized model as output feedback system is proposed. Two possible configurations of the system are presented. The use of linear adaptive systems including Kalman filter is also proposed for higher accuracy. The performances of the proposed methods are shown by numerical simulations.
雑誌名	日本ロボット学会誌
巻	13
号	1
ページ	89 - 99
発行年	1995-01
ISSN	02891824
書誌レコードID	AN00141189
フォーマット	application/pdf
日本十進分類法	548.3
出版者	日本ロボット学会