Title :
Robot motion command simplification and scaling
Author :
Young, Kuu-Young ; Liu, Shi-Huei
Author_Institution :
Dept. of Electr. & Control Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan
Abstract :
It has been observed that human limb motions are not very accurate, leading to the hypothesis that the human motor control system may have simplified motion commands at the expense of motion accuracy. Inspired by this hypothesis, we propose learning schemes that trade motion accuracy for motion command simplification. When the original complex motion commands capable of tracking motion accurately are reduced to simple forms, the simplified motion commands can then be stored and manipulated by using learning mechanisms with simple structures and scanty memory resources, and they can be executed quickly and smoothly. This paper also proposes learning schemes that can perform motion command scaling, so that simplified motion commands can be provided for a number of similar motions of different movement distances and velocities without recalculating system dynamics.
Keywords :
learning (artificial intelligence); learning systems; motion control; robot dynamics; tracking; command scaling; dynamics; learning mechanisms; motion command; motion control; robots; simplification; tracking; Control engineering; Control systems; Human robot interaction; Learning systems; Motion control; Motor drives; Muscles; Robot control; Robot motion; Tracking;
Conference_Titel :
Fuzzy Systems Conference Proceedings, 1999. FUZZ-IEEE '99. 1999 IEEE International
Conference_Location :
Seoul, South Korea
Print_ISBN :
0-7803-5406-0
DOI :
10.1109/FUZZY.1999.793275