Adaptive Niche Genetic Algorithm Based Path Planning and Dynamic Obstacle Avoidance of Mobile Robots

被引:1
作者
Zeng Dehuai [1 ,2 ]
Xie Cunxi [1 ]
Li Xuemei [1 ]
Xu Gang [2 ,3 ]
机构
[1] South China Univ China, Guangzhou 510640, Guangdong, Peoples R China
[2] Shenzhen Univ, Inst Intelligent Technol, Shenzhen 518060, Peoples R China
[3] Shenzhen Key Lab Mould Adv Mfg, Shenzhen 518060, Peoples R China
来源
2008 IEEE INTERNATIONAL CONFERENCE ON AUTOMATION AND LOGISTICS, VOLS 1-6 | 2008年
关键词
Adaptive niche genetic algorithm; optimal; path planning; obstacle avoidance;
D O I
10.1109/ICAL.2008.4636461
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Genetic Algorithms (GAs) have demonstrated to be effective procedures for solving multi criterion optimization problems. These algorithms mimic models of natural evolution and have the ability to adaptively search large spaces in near-optimal ways. One direct application of GAs is in the area of evolutionary robotics, but standard GAs have some drawbacks such as time-consuming and premature convergence. A novel robot path planning method based on Adaptive Niche Genetic Algorithm (ANGA) is first presented in this paper. To make ANGA more effective, the fitness evaluation with multi criterions is designed to fit feasible and infeasible paths. The adaptive crossover and mutation operators are trimmed to the path planning problem. The experiment results demonstrate that AGNA based path planer has more adaptability, displaying near-optimal paths in different configurations of the environment with obstacle than the standard GAs.
引用
收藏
页码:1858 / +
页数:2
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