摘要
静动态障碍物同时存在的复杂环境下进行路径规划是一个比较难解决的课题。引入双重的遗传算法机制,提出了第一重遗传机制负责静态障碍物的避碰,第二重遗传算法机制以第一重机制规划出的最优路径为基础,负责动态障碍物的避碰的方法;设计优化算子,引入自适应技术提高路径的生成速度。实验表明,该方法能综合考虑多种因素,收敛到全局最优路径。
It is a more difficult problem to plan path in environment which is with both static obstacles and dynamic obstacles. Double-layered genetic algorithm mechanism was brought up. The first layer genetic algorithm is responsible for static obstacles avoidance. The second layer genetic algorithm answers for dynamic obstacles avoidance, which is based on the first layer optimized path mechanism. Optimized operator and adaptive technology were designed to speed up creating optimized path. The result of experimentation shows that multi-factor could be calculated synthetically and the best path could be convergent by this way.
出处
《系统仿真学报》
EI
CAS
CSCD
北大核心
2008年第8期2048-2051,2091,共5页
Journal of System Simulation
基金
自主多机器人群体协作机制的协进化研究(601078)
浙江省自然科学基金
关键词
遗传算法
路径规划
适应度函数
自适应
Genetic Algorithm
path planning
fitness function
adaptive
