DocumentCode
401566
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
Volume
2
fYear
2003
fDate
2-5 Nov. 2003
Firstpage
698
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2003 International Conference on
Print_ISBN
0-7803-8131-9
Type
conf
DOI
10.1109/ICMLC.2003.1259565
Filename
1259565
Link To Document