Aiming at the slow running speed of PRM algorithm and the difficulty of sampling in narrow channel,a grid probabilistic path map algorithm was proposed.The grid was used to divide the map,and according to the area of obstacles in the grid,the threat level of the grid was divided,and different sampling strategies were used accordingly.A resampling method was proposed to improve the sampling efficiency and increase the sampling times in narrow channel.When connecting the sampling points,it did not traverse all the points,only the nearby grid was connected.After the path was generated,the path was optimized and smoothed to improve the path quality and to make it conform to the motion constraints of the mobile robot.Through simulation analysis,the basis of selecting the grid scaling factor k in the grid probabilistic path graph method was obtained.The simulation results show that the grid probabilistic path graph algorithm is better than PRM algorithm in terms of operation time and success rate.