Time-optimal trajectory planning for 6R manipulator arm based on chaotic improved sparrow search algorithm

Purpose Trajectory planning is a core aspect of manipulator operation, directly influencing its performance. This paper aims to introduce a chaotic improved sparrow search algorithm (CISSA) to optimize hybrid polynomial-interpolated trajectories, enhancing the efficiency and precision of manipulator trajectory planning. Design/methodology/approach The proposed approach leverages 3-5-3 polynomial interpolation to construct the motion trajectory of a 6R manipulator. To optimize the trajectory over time, the sparrow search algorithm is enhanced with chaotic mapping, a discoverer dispersion strategy, positional limiting mechanisms and Brownian motion. These enhancements collectively reduce the manipulator’s runtime while meeting operational requirements. Findings The proposed method was applied to the AUBO-i5 robot to evaluate its performance. Simulation results demonstrate that CISSA effectively avoids local optima and achieves more accurate solutions compared to similar algorithms. By integrating CISSA into trajectory planning, the robot’s movement time was reduced by 13.99% compared to the original SSA, and the number of algorithm iterations was significantly decreased, ensuring smoother and more efficient task execution in real production. Originality/value A CISSA is proposed and applied to the optimal time trajectory planning of the manipulator, verifying the effectiveness and superiority of the algorithm. Experimental results show that CISSA outperforms comparable algorithms by several orders of magnitude in solving manipulator inverse kinematics, significantly enhancing planning efficiency and reducing trajectory planning time.