Abstract: In order to solve the problems of unreasonable trajectory planning of rescue robot manipulator arm and slow convergence speed of the planning method in the complex environment of coal mines, a trajectory planning algorithm of manipulator arm of coal mine rescue robot based on grey wolf optimization with cuckoo search(CS-GWO)is proposed.With the quintic polynomial interpolation as the basic trajectory planning method, the trajectory planning is carried out in the manipulator arm joint space, and the obtained trajectory is optimized by the CS-GWO algorithm to realize the time-energy optimal trajectory planning of the manipulator arm.The CS-GWO algorithm integrates the two perturbation process of the cuckoo search(CS)algorithm into the position update method of the grey wolf optimization(GWO)algorithm.Combined with the Lévy flight mode of the CS algorithm and the characteristics of the random update of the nest position, the algorithm enables the wolves to randomly jump out of the local search area in the process of approaching the prey, expands the search range, avoids the algorithm from falling into the local optimal solution, and enhances the GWO algorithm's global search capability.Matlab simulation results show that the CS-GWO algorithm can improve the convergence speed of the CS algorithm and the global search capability of the GWO algorithm effectively, with better stability and better overall performance.The use of the manipulator arm trajectory planning algorithm can obtain a time-energy optimal trajectory.The curves of angular displacement, angular velocity, and angular acceleration of each joint are smooth and continuous, which solves the optimal trajectory planning problem of manipulator arm of rescue robot in the complex environment of coal mines effectively.