標題: Robot motion similarity analysis using an FNN learning mechanism
作者: Young, KY
Wang, JK
電控工程研究所
Institute of Electrical and Control Engineering
關鍵字: robot learning control;learning space complexity;motion similarity analysis;fuzzy neural network
公開日期: 1-Dec-2001
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 excessive amount of memory when they are employed as major roles in motion governing. We propose using a fuzzy neural network (FNN) to learn and analyze robot motions so that 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. (C) 2001 Elsevier Science B.V. All rights reserved.
URI: http://dx.doi.org/10.1016/S0165-0114(00)00081-6
http://hdl.handle.net/11536/29238
ISSN: 0165-0114
DOI: 10.1016/S0165-0114(00)00081-6
期刊: FUZZY SETS AND SYSTEMS
Volume: 124
Issue: 2
起始頁: 155
結束頁: 170
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