基于优化人工蜂群算法的多机器人协同规划

Multi-robot Collaborative Planning based on Optimized Artificial Bee Colony Algorithm

为了提高人工蜂群算法在多机器人路径规划中的性能,提出了优化人工蜂群算法。提出了一种新的环境建模方法,将障碍物边缘平滑化;分析了人工蜂群算法原理,改进了新食物源的生成方法,提出了自适应的搜索因子,兼顾了大范围搜索和算法收敛速度;改进了机器人路径点的表示方法,使用位置夹角表示机器人路径点,减少了位置参数;使用加权方式将路径长度、路径平滑度、路径安全性综合为目标函数。仿真实验结果表明,改进在多机器人路径规划中不仅耗时较少,而且路径也短,且随着机器人数量的增加,耗时和路径长度的差距越来越大。

To improve property of artificial bee colony algorithm in multi - robot path planning, the opti- mized artificial bee colony algorithm is proposed. A new environment modeling method is given, which makes barrier border smooth. The principle of artificial bee colony algorithm is analyzed, adaptive searching factor is proposed to improve new food source generation method, which balances searching range and convergence rate. The robot path point is improved by location angle, and by using this way, the location parameter is reduced. The path length, path smoothness and path safety is synthesized to a goal function by weight. The simulation tri- al shows that path length and time cost of improved algorithm is superior to primary algorithm. And with robot quantity increasing, the gap of the two algorithms is bigger and bigger.