针对多机器人多目标路径规划问题，提出基于算法融合的多机器人多目标路径规划算法.算法采用改进A^*算法进行全局路径规划，采用改进模拟退火算法规划多机器人在组合全局路径最优的情况下，保证最远机器人路径最短，采用DWA算法进行局部路径规划，实现机器人局部运动避障.为了验证所提算法的可行性和优越性，对其进行仿真实验，实验结果表明，改进A^*算法比经典A^*算法在转弯次数、转弯角度、遍历节点、规划距离分别减少16.66%、41.24%、23.3%、0.77%，改进模拟退火算法与传统模拟退火算法在仿真时间、最长路径长度、总路径分别减少12.09%、22.26%、5.74%，DWA算法能够实现多机器人局部路径规划与避障.

Aiming at the problem of multi - robot multi - objective path planning， a multi - robot multi - objective path planning algorithm based on algorithm fusion is proposed. The algorithm adopts the improved A^* algorithm for global path planning， the improved simulated annealing algorithm for planning multiple robots to ensure the shortest path for the farthest robot in the case of combining the optimal global paths， and uses the DWA algorithm for local path planning to realize the local motion obstacle avoidance of robots. In order to verify the feasibility and superiority of the proposed algorithm， simulation experiments are carried out. The experimental results show that the improved A^* algorithm reduces the number of turns， turning angles， traversal nodes， and planned distance by 16.66%， 41.24%， 23.3%， and 0.77% respectively compared to the classical A^* algorithm. The improved simulated annealing algorithm reduces simulation time， longest path length， and total path by 12.09%， 22.26%， and 5.74% respectively compared to the traditional simulated annealing algorithm. The DWA algorithm can achieve multi robot local path planning and obstacle avoidance.