Adaptive Genetic Algorithm Enhancements for Path Planning of Mobile Robots

摘要：

An adaptive Genetic Algorithm (GA) is proposed, which focuses on the automatic adjustments of crossover probability and mutation probability with the changeable environmental parameters. The improved algorithm can overcome some disadvantages of traditional GA, such as, early falling into local optimum, lower convergence speed and large calculation etc. In sequence, the complementary characteristic between crossover probability and mutation probability is obtained through carrying out the numerical simulation. The results demonstrate that, compared with the traditional GA, the adaptive one leads to better performance in path curves and fitness, when 30 generations operations is implemented.This solution mentioned above, is proved to a better choice for practical application in path planning for mobile robots.

关键词： Mobile Robot Adaptive GA Path Planning crossover probability mutation probability

作者: Wang Jianguo Zhang Yilong Xia Linlin

作者单位: Northeast Dianli University School of Automation Engineering, Jilin City, Jilin, 132012, China

会议类型: 国际会议

会议名称: 2010 International Conference on Measuring Technology and Mechatronics Automation(ICMTMA 2010)(2010年检测技术与机电自动化国际会议)

会议地点: 长沙

会议语种:英文

页码: 416-419

在线出版日期: 2010-03-13（万方平台首次上网日期，不代表论文的发表时间）