Title :
Ant Colony System Based Mobile Robot Path Planning
Author :
Chia, Song-Hiang ; Su, Kuo-Lan ; Guo, Jr-Hung, Jr. ; Chung, Cheng-Yun
Author_Institution :
Dept. of Electron. Eng., Wu-Feng Inst. of Technol., Chiayi, Taiwan
Abstract :
Ant colony optimization (ACO) is a new evolvement algorithm that is proposed by Dorigo M., and solves some task allocation and target search problems to program the motion path searching food. The topic of the article uses the ant colony optimization algorithm to mobile robot system, and solve the problem of mobile robot path planning such that the target point in a collision free space. The simulated results presents that ACO can finds the optimization motion path for mobile robot moving to the target position (food) from the start position (nest) in a collision-free environment.
Keywords :
collision avoidance; mobile robots; motion control; search problems; ant colony optimization algorithm; ant colony system; collision-free environment; evolvement algorithm; mobile robot path planning; target search problems; task allocation problems; Ant colony optimization; Conferences; Mobile robots; Optimization; Path planning; Resource management; Ant colony optimization; collision-freee; task allocation;
Conference_Titel :
Genetic and Evolutionary Computing (ICGEC), 2010 Fourth International Conference on
Conference_Location :
Shenzhen
Print_ISBN :
978-1-4244-8891-9
Electronic_ISBN :
978-0-7695-4281-2
DOI :
10.1109/ICGEC.2010.59
