Robot path planning is an important research area for achieving efficient navigation in mobile robotics. For solve the problem that traditional optimization algorithm slow convergence in complex environment, this paper proposes a Multi-strategy Improved Sparrow Search Algorithm (MSISSA). First, aiming at the problem of inadequate population initialization, the Circle chaotic mapping is added. Second, aiming at the problem of insufficient searching ability of algorithm, a spiral search strategy simulating spiral trajectories is introduced, it can enhance the searching ability and optimization ability of the algorithm. Finally, a triangular random walk strategy is applied in the later optimization stage to perform random searches, it can effectively improve the local development ability of the algorithm. The MSISSA is validated using standard test functions. The MSISSA shows excellent convergence speed and optimization effect in these eight test functions compared with other classical algorithms. In this paper, MSISSA is also simulated in raster map, the experimental results show that MSISSA has better optimization effect in path planning.