目的 以应用于包装车间的移动机器人的路径规划作为研究对象，解决蚁群算法收敛速度慢、寻找到的路径不优等缺陷。方法 引入改进烟花和蚁群融合的方法进行搜索，首先建立移动机器人的栅格地图，其次采用改进烟花算法进行路径粗搜索，将得到的路径作为信息素增量，再运用蚁群细搜索求解。结果 文中方法与传统方法相比，收敛速度得到提高，并寻找到了更优的路径。结论 通过采用融合算法，弥补了烟花寻优的不足，加快了蚁群的收敛，可以对2种算法互相取长补短。

The paper aims to solve the slow convergence speed and inferior path of ACO algorithm with the path planning of mobile robot applied in packaging workshop as the research object. The method of fusing IFWA and ACO was applied for searching. Firstly, the raster map of mobile robot was established. Secondly, the IFWA was used to search the path roughly to take the path obtained as the pheromone increment. Then the ACO subtle search was used for solution. Compared with the traditional method, the method adopted in this paper improved the convergence speed and found the optimal path. The proposed fusion method covers the shortage of FWA and accelerates the convergence of ACO. The two algorithms could be used for mutual complementation.