Title :
Joint parameters identification for redundant manipulators based on fuzzy theory and genetic algorithm
Author :
Li, Yangmin ; Liu, Xiaoping ; Peng, Zhaoyang ; Liu, Yugang
Author_Institution :
Fac. of Sci. & Technol., Univ. of Macau, Macao, China
Abstract :
The joint parameters of redundant manipulators are prerequisite data for effective dynamics control. An identification method via fuzzy theory and genetic algorithm has been presented to study modular redundant robots. The genetic algorithm is used in the fuzzy optimization expecting to obtain global optimal solutions. Experimental modal analysis and finite element method have been exploited in dynamics modeling. The joint parameters of a 9-DOF modular redundant robot have been identified.
Keywords :
finite element analysis; fuzzy set theory; genetic algorithms; manipulator dynamics; parameter estimation; redundant manipulators; 9-DOF modular redundant robot; dynamics modeling; effective dynamics control; finite element method; fuzzy optimization; fuzzy theory; genetic algorithm; global optimal solutions; joint parameters identification; modal analysis; modular redundant robots; modular robot; parameter identification; redundant manipulators; Analytical models; Damping; Genetic algorithms; Manipulator dynamics; Modal analysis; Parameter estimation; Robotics and automation; Robots; Solid modeling; Vibration control;
Conference_Titel :
Electrical and Computer Engineering, 2002. IEEE CCECE 2002. Canadian Conference on
Print_ISBN :
0-7803-7514-9
DOI :
10.1109/CCECE.2002.1015288
