標題: Similarity analysis for robot motions using an FNN learning mechanism
作者: Young, KY
Wang, JK
電控工程研究所
Institute of Electrical and Control Engineering
公開日期: 1997
摘要: Learning controllers are usually subordinate to conventional controllers in governing multiple-joint robot motion, in spite of their ability to generalize, because learning-space complexity and motion variety require them to consume exccessive amount of memory. We propose using a Fuzzy Neural Network (FNN) to learn and analyze robot motions so they can be classified according to similarity. After classification, the learning controller can then be designed to govern robot motions according to their similarities without consuming excessive memory resources.
URI: http://hdl.handle.net/11536/19645
ISBN: 0-7803-4187-2
ISSN: 0191-2216
期刊: PROCEEDINGS OF THE 36TH IEEE CONFERENCE ON DECISION AND CONTROL, VOLS 1-5
起始頁: 2523
結束頁: 2528
Appears in Collections:Conferences Paper