Abstract: To address the inefficiency and instability in robotic arm joint movements during optimal time trajectory planning, we introduce a novel planning strategy based on an adaptive chaotic sparrow search algorithm. First, during the trajectory planning process, the duration of each phase is optimized regarding the constraints of the angle, angular velocity, and angular acceleration of each joint. Trajectory points are interpolated using the 4-5-4 polynomial interpolation algorithm. Second, the Tent lens inverse imaging strategy, adaptive weight strategy, and Cauchy mutation strategy are incorporated into the traditional sparrow search algorithm to improve its convergence accuracy and convergence speed. Finally, experimental verification is conducted using a 6-degree-of-freedom manipulator. Simulation results indicate a significant reduction in the running time of the manipulator and smoother operation achieved with the improved algorithm for trajectory planning.