重庆理工大学学报(自然科学) ›› 2024, Vol. 38 ›› Issue (1): 368-378.

• “智能机器人感知、规划及应用技术”专栏 • 上一篇    

改进粒子群算法在六轴机械臂关节空间轨迹规划中的应用

杜超斐,刘睿,丁军,黄霞,金辉   

  1. 重庆理工大学机械工程学院
  • 出版日期:2024-02-07 发布日期:2024-02-07
  • 作者简介:杜超斐,男,硕士研究生,主要从事智能机器人、机械臂运动规划研究,Email:17635043507@163.com。

Spatial trajectory planning method for joints of six-axis robotic arm based on improved particle swarm algorithm

  • Online:2024-02-07 Published:2024-02-07

摘要: 以xArm6机械臂为研究对象,提出了一种基于改进粒子群算法的时间最优353分段多项式插值的关节空间轨迹规划方法。该方法以机械臂运行时间最优为目标,在满足速度、加速度及变加速度的约束条件下,用引入了自适应惯性权重以及概率突跳特性的改进粒子群算法对各段插值时间进行优化。相比于传统粒子群算法,改进的粒子群算法迭代速度更快,同时不易陷入局部最优。仿真结果表明,机械臂运行平稳,且6个关节的位置、速度、加速度连续无突变,证明该方法有效可行。

关键词: 6自由度机械臂, 改进粒子群算法, 轨迹规划, 时间最优, 多项式插值

Abstract: This paper takes the xArm6 robotic arm as the research object and proposes a joint space trajectory planning method based on the time-optimal 3-5-3 segmented polynomial interpolation of the improved particle swarm algorithm. The proposed method improves the operation efficiency and stability of the six-axis robotic arm. It takes the optimal running time of the robotic arm as the objective, and under the constraints of speed, acceleration and variable acceleration, the interpolation time of each segment is optimized by the improved particle swarm algorithm which introduces adaptive inertia weights and probabilistic jump characteristics. Compared with the traditional particle swarm algorithm, the improved particle swarm algorithm reaches a faster iteration speed and is less likely to fall into local optimum. Our results of robotic arm motion simulation show the robotic arm operates smoothly, and the six joints experience not abrupt, but continuous changes in positions, velocities and acceleration, demonstrating the practicality and effectiveness of the method.

中图分类号: 

  • TP242