Rough set and genetic algorithm in path planning of robot

Abstract

A hybrid method of rough set and genetic algorithms is presented to raise the speed and accuracy of path planning of robot. Firstly, gain the decision rule by rough set theory. And then, come to a series of available paths by training the gained minimal decision rule. Finally, optimize the population of the paths above using genetic algorithms, and obtain the most excellent path. The results show that the hybrid method is good at raising the speed of path planning of robot.