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Path planning is mine rescue detection of autonomous navigation key steps, mine is three dimensional non institutional environment, the robot walk process should be highly intelligent path planning, the traditional adaptive ability and processing nonlinear problem ability is bad, the error is bigger, path planning of coal mine underground robot based on parallel particle swarm optimization is proposed. Fully consider down hole environment height change, the grid method is adopted to environment modeling, particle swarm independent distribution in different containers are path modeling, different containers particle separately optimization operation, because of the speed and the most optimal group were retained in robot path planning, the experimental stage, path planning time reduced by 20% than the traditional methods, obstacle avoidance success rate reaches as high as 95%, the optimal path appear probability can maintain at 99%, this method has a strong guidance and practical value.