Abstract: Aiming at the problem of insufficient operation efficiency in traditional mobile manipulator path planning due to the neglect of the spatial distribution of grasping points and the correlation with the coordinates of workstations, a time-optimal trajectory planning method integrating an improved particle swarm optimization algorithm is proposed. This method uses 3-5-3 piecewise polynomial interpolation to construct a multi-objective optimization model, focusing on optimizing two key indicators: trajectory execution time and movement speed. By introducing a nonlinear dynamic adjustment mechanism, the inertia weight and acceleration factor are adaptively adjusted, significantly enhancing the algorithm's global optimization ability and convergence characteristics. The results show that, compared with the standard particle swarm algorithm, this method has a significant advantage in optimizing the movement time of each joint of the manipulator, with overall system execution efficiency improved by 67%. This fully verifies the effectiveness of the proposed algorithm in the field of industrial robot path planning.