Abstract: Aiming at the problem of time-optimal trajectory planning for manipulators in joint space, a time-optimal trajectory planning method for manipulators based on the improved moss growth optimization (IMGO) algorithm is proposed. Taking the UR5 6-degree-of-freedom manipulator as the simulation research object, a time-optimal mathematical model based on 3-5-3 hybrid polynomial interpolation is constructed, and the IMGO algorithm is used for trajectory optimization. By introducing chaotic initialization, Lévy flight strategy, and joint opposition selection operator, the global search ability and convergence accuracy of the algorithm are improved. Comparisons are made with the standard moss growth optimization (MGO) algorithm, standard particle swarm optimization (PSO) algorithm, and elephant herding optimization (EHO) algorithm. The simulation results show that compared with other optimization algorithms, the operation time of the manipulator using the IMGO algorithm is reduced by 6.7%, 17.1%, and 21.1% respectively. Moreover, it also performs best in terms of convergence speed and stability. The displacement, velocity, and acceleration curves of each joint are smooth, satisfying the kinematic constraints of the manipulator. The proposed method provides a new solution for efficient trajectory planning of manipulators and verifies the application potential of the algorithm in the industrial field.