NDLI: Intelligent control of a 7-DOF manipulator based on model primitives

Content Provider	IEEE Xplore Digital Library
Author	Thrishantha Nanayakkar, D.P. Watanabe, K. Kiguchi, K. Shadmehr, R.
Copyright Year	2002
Description	Author affiliation: Dept. of Biomed. Eng., Johns Hopkins Univ. Sch. of Med., Baltimore, MD, USA (Thrishantha Nanayakkar, D.P.)
Abstract	This paper presents a method to control industrial redundant manipulators based on a method similar to the mechanism ascribed to the human motor system that adaptively combines motor primitives to control human body motions. The idea is to identify a set of local model primitives based on Runge-Kutta-Gill neural networks (RKGNNs) and control the manipulator based on an adaptive selection and fusion method. The adaptive selection is carried out using a resonance signal that recalls only the most relevant memory primitives given a situation, and adaptive fusion is carried out by a method based on fuzzy memberships. This method imitates few recent findings on how human motor skills are developed by adaptive combination of motor primitives. Experiments on an industrial manipulator with seven degrees of freedom shows that the proposed method is a potentially viable approach to model based control of redundant robot manipulators.
Starting Page	538
Ending Page	543
File Size	627062
Page Count	6
File Format	PDF
ISBN	078037620X
ISSN	21589860
DOI	10.1109/ISIC.2002.1157820
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-10-30
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Intelligent control Humans Biological system modeling Motion control Control systems Industrial control Manipulators Electrical equipment industry Neural networks Programmable control
Content Type	Text
Resource Type	Article

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