Improvement on RobotsPositioning Accuracy Basedon Genetic Algorithm
BinLiang YuLiu · 2006
Thepaper analyzes therobot link's positioning errorsources andbuilds itserrormodelofgeometrical parameters. Withtheaidofthegenetic algorithm (GA)that hasthepowerful global adaptive probabilistic search ability, 24 parameters ofa 6-DOFrobotareidentified through simulation, whichmakestherobot's position andorientation accuracy angreat improvement. Intheprocess oftherobot calibration, stochastic measurement noises areconsidered. Thesimulation results showthat withGA calibrating therobot isa kindofsuperior method, eveniftherobotlink's parameters arerelative, GA still hassearch ability tofind the optimum solution.