目的 为了提高阀口袋套袋机器人的工作效率，提出基于改进粒子群算法的阀口袋套袋机器人时间最优轨迹规划方法。方法 首先，通过逆运动学方程反解出操作空间轨迹对应的关节空间角度值。其次，采用4–3–4混合多项式对阀口袋套袋机器人的关节空间轨迹进行插值拟合。最后，在速度约束条件下，利用改进粒子群算法对阀口袋套袋机器人的运行时间进行优化处理。结果 仿真结果表明，改进粒子群算法可以在保证阀口袋套袋机器人运行平稳的条件下将总运行时间缩减41.66%，实现了阀口袋套袋机器人在关节空间中时间最优的轨迹规划。结论 该方法可有效地提高机器人工作效率，延长机器人的使用寿命，为阀口袋套袋机器人稳定可靠运行提供了科学依据。

The work aims to propose a time-optimal trajectory planning method for the valve pocket bagging robot based on improved particle swarm optimization algorithm, so as to improve the working efficiency of the robot. Firstly, the joint space angle corresponding to the trajectory of the operating space was solved by the inverse kinematics equation. Then, the joint space trajectory was fitted by 4-3-4 mixed polynomial interpolation method. Finally, the improved particle swarm optimization algorithm was used to optimize the running time of the valve pocket bagging robot under the speed constraints. From the simulation results, the improved particle swarm optimization algorithm could reduce the total running time by 41.66% under the condition of ensuring the smooth running of the valve pocket bagging robot, and realize the time-optimal trajectory planning of the valve pocket bagging robot in joint space. The method can effectively improve the working efficiency of the robot, prolong the service life of the robot, and provide a scientific basis for the stable and reliable operation of the valve pocket bagging robot.