Title :
Rough set and genetic algorithm in path planning of robot
Author :
Zhang, Ying ; Wu, Chengdong ; Li, Mengxin
Author_Institution :
Shen Yang Archit. & Civil Eng. Inst., Shenyang, China
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.
Keywords :
genetic algorithms; path planning; robots; rough set theory; decision rule; genetic algorithm; path planning; robot; rough set theory; Artificial intelligence; Civil engineering; Fuzzy logic; Genetic algorithms; Gradient methods; Knowledge representation; Machine learning; Path planning; Robots; Set theory;
Conference_Titel :
Machine Learning and Cybernetics, 2003 International Conference on
Print_ISBN :
0-7803-8131-9
DOI :
10.1109/ICMLC.2003.1259565