DocumentCode :
2447332
Title :
Learning gait patterns for the fuzzy synthesis of piped walk
Author :
Magdalena, Luis ; Monasterio, Félix
Author_Institution :
ETSI Telecomunicacion, Univ. Politecnica de Madrid, Spain
fYear :
1994
fDate :
18-21 Dec 1994
Firstpage :
248
Lastpage :
250
Abstract :
The gait synthesis is one of the tasks that must be performed by the controller of a biped walking machine. A fuzzy logic controller (FLC) has been designed to perform this task. The initial rules have been obtained from biomechanical studies using the description of human limb motion during walking, given by different authors. A learning mechanism has been added to the FLC. A walk can be viewed as a sequence of steps, and each step is a cyclical and repeatable trajectory in the state space. We can relate this trajectory in the state space with a gait pattern that is described by a set of fuzzy rules (a gait description). Using this set of rules as a piece of knowledge, we define a pattern learning mechanism, based on an evolution system
Keywords :
fuzzy control; fuzzy logic; learning (artificial intelligence); pattern recognition; biomechanical studies; biped walking machine; controller; cyclical trajectory; evolution system; fuzzy logic controller; fuzzy rules; fuzzy synthesis; gait description; gait patterns learning; human limb motion; learning mechanism; pattern learning mechanism; repeatable trajectory; Control system synthesis; Foot; Fuzzy logic; Fuzzy sets; Fuzzy systems; Learning systems; Legged locomotion; Mechanical variables control; State-space methods; Telecommunication control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Information Processing Society Biannual Conference, 1994. Industrial Fuzzy Control and Intelligent Systems Conference, and the NASA Joint Technology Workshop on Neural Networks and Fuzzy Logic,
Conference_Location :
San Antonio, TX
Print_ISBN :
0-7803-2125-1
Type :
conf
DOI :
10.1109/IJCF.1994.375128
Filename :
375128
Link To Document :
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