Applying Improved Particle Swarm Optimization Algorithm to Trajectory Planning of Manipulator

谢嘉; 吴家桢; 李永国; 梁锦涛

doi:10.13433/j.cnki.1003-8728.20230099

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Applying Improved Particle Swarm Optimization Algorithm to Trajectory Planning of Manipulator

更新时间：2026-07-10

- Applying Improved Particle Swarm Optimization Algorithm to Trajectory Planning of Manipulator
- Mechanical Science and Technology for Aerospace Engineering Vol. 43, Issue 10, Pages: 1681-1686(2024)
- 作者机构：
  
  1. 上海海洋大学机构工程学院,上海,201306
  2. 西安电子科技大学机电工程学院,西安,710071
- 作者简介：
- 基金信息：
- DOI：10.13433/j.cnki.1003-8728.20230099
  CLC： TP241;TP18
- Published：2024
- 稿件说明：
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谢嘉, 吴家桢, 李永国, et al. Applying Improved Particle Swarm Optimization Algorithm to Trajectory Planning of Manipulator[J]. Mechanical Science and Technology for Aerospace Engineering, 2024, 43(10): 1681-1686.
DOI：

谢嘉, 吴家桢, 李永国, et al. Applying Improved Particle Swarm Optimization Algorithm to Trajectory Planning of Manipulator[J]. Mechanical Science and Technology for Aerospace Engineering, 2024, 43(10): 1681-1686. DOI： 10.13433/j.cnki.1003-8728.20230099.

摘要

针对机械臂运动效率与稳定性问题，提出了一种基于改进粒子群算法的时间优化轨迹规划方法。该方法以3-5-3组合分段多项式插值算法为基础，以分段区间的时间为优化目标，通过带有动态学习因子与收缩因子的改进粒子群优化算法进行优化。本文以实验室的空中作业机器人作业机械臂为模型，将本文方法与标准粒子群优化规划方法进行比较，仿真结果证明该方法收敛速度和精度都有明显改善，且算法未陷入局部收敛，最终优化结果有12.8%的提升。在该轨迹下机械臂的关节角度、速度、加速度曲线平滑无突变，机械臂运动平稳，方法具有可行性。

Abstract

In order to plan the time-optimal trajectory of the working manipulator of an aerial work robot

a time-optimal 3-5-3 combined piecewise polynomial interpolation algorithm based on the improved particle swarm optimization algorithm is proposed. First

a 3-5-3 combined piecewise polynomial is constructed. Then

under the constraints of angular velocity and angular acceleration

taking the shortest time as the optimization goal

the improved particle swarm optimization algorithm is used to optimize the results of the combined piecewise polynomial. Finally

the simulation results show that compared with the standard particle swarm optimization algorithm

the improved particle swarm optimization algorithm has significantly improved convergence speed and accuracy and does not fall into local convergence. The final optimization result is 12.8% higher than that of the standard algorithm. Under this trajectory

the joint angle

velocity and acceleration curves of the manipulator are smooth without sudden change. The motion of the manipulator meets the requirements

indicating that the improved algorithm is feasible.

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