改进萤火虫算法求解多机器人路径规划

为解决多机器人在静态环境中的路径规划问题，以路径长度为优化目标模型，并针对此模型设计了多机器人萤火虫算法(MR-FA)。首先，考虑到路径安全性对环境中的障碍物采取扩张操作，设计初始化规则以提高生成初始种群的效率；其次，根据算法的连续性原理及特点，设计个体等长策略将维度不一致的个体转变为等维度个体以便于萤火虫的移动更新，并对移动更新后的不可行解采取路径修正策略；然后对规划出的每个机器人的移动路径进行碰撞检测，同时针对机器人不同的碰撞情况设计相应的避碰策略，即暂停—回退策略(PFS)、局部路径重规划策略(LPRS);最后，为验证MR-FA的有效性，在三组环境中进行仿真实验并与其他三种算法进行对比，综合得出MR-FA在解决多机器人路径规划时更有优势。

Improved firefly algorithm for multi-robot path planning

In order to solve the path planning problem of multi-robots in static environment, the path length was used as the optimization target model, and this paper designed a multi-robot firefly algorithm(MR-FA) for this model. Firstly, considering the path security to expand the obstacles in the environment, MR-FA designed an initialization rule to improve the efficiency of generating the initial population. Secondly, according to the continuity principle and characteristics of the algorithm, it designed an individual isometric strategy to convert individuals with inconsistent dimensions into equal-dimensional individuals to facilitate the mobile update of fireflies, and designed initialization rules to improve the efficiency of generating initial populations. Then, it performed collision detection on the planned movement path of each robot, and designed corresponding collision avoidance strategies for different collision situations of robots: pause-fallback strategy(PFS), local path replanning strategy(LPRS). Finally, this paper carried out the simulation experiments in three groups of environments and compared the effectiveness of MR-FA with the other three algorithms. It can be concluded that MR-FA has more advantages in solving multi-robot path planning.