Abstract: The existing path planning algorithm of robot in coal mine uses fixed step size and serial mode to generate path, which has problems such as low success rate, poor real-time performance and low efficiency.Combining membrane computing(MC)with Informed RRT^* algorithm, this study proposes a path planning algorithm of robot in coal mine, namely MC-IRRT^* algorithm.The algorithm is divided into two stages, namely fast connectivity and path optimization.In the fast connectivity stage, the multi-step cellular membrane structure is constructed, and the step size is adjusted according to the size of the space area.The large step search is used in the area with larger feasible space to accelerate the search speed.The small step search is used in the narrow space to make the search space more refined and improve the success rate of the narrow space path search.In the path optimization stage, a multi-sampling cellular membrane structure is constructed, and multiple basic membranes are calculated in parallel, and the shortest feasible path is searched in parallel in multiple elliptical areas at the same time to save time and improve the efficiency of path optimization.The simple scene experimental results show that compared with Informed RRT^* algorithm, the search efficiency of MC-IRRT^* algorithm in the fast connectivity stage and the path optimization phase is increased by 76% and 40% respectively.The complex scene experimental results show that the path planning of RRT^* algorithm and Informed RRT^* algorithm fails, and both PQ-RRT^* algorithm and MC-IRRT^* algorithm can find feasible paths successfully.Compared with PQ-RRT^* algorithm, the rate of MC-IRRT^* algorithm is increased by 12.79%, and the planned path length is shortened by 8.18%.The MC-IRRT^* algorithm can not only pass through narrow feasible areas quickly, but also can choose to use smaller step at the turning point of the path so as to make the path smoother.