摘要
针对现代移动机器人路径规划中的蚁群算法收敛速度比较慢,并且容易陷入局部最优的问题中,提出了基于势场蚁群算法的多机器人编队研究。此算法通过机器人、人工势场力和目标的距离时间机器人移动及避障综合启发信息的创建,并且通过蚁群搜索机制处于未知环境中,对机器人通过起始位置到目标位置全局的最优路径进行寻找。所提出的算法能够有效结合人工势场法及蚁群算法,从而有效提高传统蚁群算法对于最优路径搜索的效率。最后,利用仿真实验对提出算法在机器人编队规划过程中的有效性进行了全面的仿真。
For the slow convergence rate of ant colony algorithm in the path planning of modern mobile robot,it is easy to fall into the local optimal problem.We think it proposes a multi robot formation on potential field ant colony algorithm.This algorithm was created by robot,artificial potential field force and target distance time,including robot movement and obstacle avoidance in comprehensive heuristic information.Moreover,we,through the ant colony search mechanism,think it was in the unknown environment to search for the optimal path from the starting position to the target position of the robot.The proposed algorithm could effectively combine the artificial potential field method and the ant colony algorithmto improve the efficiency of optimal path search ofthe traditional ant colony algorithm.
作者
周祖坤
ZHOU Zukun(Kunming Metallurgy College,Kunming,Yunnan 650033,China)
出处
《中国锰业》
2018年第3期182-187,共6页
China Manganese Industry
基金
云南省教育厅基金项目(2014Y495)
关键词
势场
蚁群算法
多机器人
编队
Potential field
Ant colony algorithm
Multi robot
Formation
