摘要
为解决大量复杂凹形障碍环境中的路径规划问题,采用了计算机仿真技术,对双蚁群完全交叉算法进行了研究。通过对传统蚁群算法增加新型的距离改变启发因子,建立双蚁群完全交叉算法,并且融入最大最小蚁群算法思想,使蚁群算法应用在机器人路径规划领域,即使机器人环境中有大量复杂的凹形障碍,该算法仍能够规划出高质量的路径。仿真试验表明该算法得到最优路径率达到98%。
In order to solve the problems for path planning in concave obstacle environment, an double ant colony algorithm was completed using computer simulation technology. Combining the thought of MAX-MIN ant colony algorithm and adding new type heuristic gene based on distance change, we founded a complete cross double ant colony algorithm and applied it to robot path planning. Even when there are lots of concave obstacles in the robot environment, the algorithm still can get a high quality path and is suitable for robot path planning. The simulation results show that the best path rate obtained by the double ant colony algorithm is 98%.
出处
《农业机械学报》
EI
CAS
CSCD
北大核心
2008年第7期149-153,共5页
Transactions of the Chinese Society for Agricultural Machinery
基金
安徽省科技攻关计划项目(项目编号:07010201011)
关键词
全局路径规划
双蚁群算法
凹形障碍
启发因子
Global path planning, Double ant colony algorithm, Concave obstacle, Heuristicgene
