Bibliographic Details
| Title: |
基于粒子群算法的六轴机械臂时间最优轨迹规划库设计与应用. (Chinese) |
| Alternate Title: |
Design and Application of a Time-Optimal Trajectory Planning Library for Six-Axis Robotic Arms Based on Particle Swarm Optimization. (English) |
| Authors: |
李纪松, 陈为 |
| Source: |
Machine Tool & Hydraulics; 2026, Vol. 54 Issue 11, p53-60, 8p |
| Subject Terms: |
Particle swarm optimization, Industrial robots, Robot motion, Digital computer simulation, Software libraries (Computer programming), Servomechanisms |
| Abstract (English): |
To address the problems of the complexity and large computational load of particle swarm optimization algorithms in time-optimal trajectory planning for six-axis robotic arms, an improved particle swarm optimization time-optimal trajectory planning method was proposed. Based on a 3-5-3 piecewise polynomial, an improved particle swarm optimization (PSO) algorithm was designed. A tunable rate parameter h was introduced into the learning factors to adjust the rate at which particles transitioned from "individual exploration" to "group learning". The accuracy and running speed of the proposed algorithm were compared with those of traditional PSO, hybrid PSO, and trigonometric PSO. In combination with the widely used PLC control software CODESYS, a trajectory planning algorithm function library was designed and encapsulated. Using the D-H parameters of the ARB1410 robotic arm, an axis group model was configured to simulate the motion control of the manipulator. The simulation results show that after optimization by the improved PSO, the total motion time of the manipulator through all path points is reduced from 9 s to 5.83 s. The position curves of each joint are observed to be smooth without abrupt changes, and both the velocity and acceleration are found to be within the constraints. Under similar optimization performance, compared with hybrid PSO, the running time of the improved PSO is reduced from 1.25 s to 0.97 s. Finally, a servo experiment was carried out using the Weichuang AD70 series servo motors and drivers. The motor motion curves obtained by the Trace tool are found to be consistent with the simulation data, which verifies the smoothness of the trajectory and the effectiveness of the algorithm. [ABSTRACT FROM AUTHOR] |
| Abstract (Chinese): |
针对六轴机械臂时间最优轨迹规划中粒子群算法复杂、计算量大的问题, 提出一种改进的粒子群时间最优轨迹规划方法。基于 3-5-3 分段多项式, 设计改进的粒子群算法 (PSO), 在学习因子中引入可调变化率参数 h, 调节粒子从 "个体探索"转向"群体学习"的速率, 并分别与传统 PSO、混合 PSO 及三角函数 PSO3 种算法的精度与运行速度进行对比。结合目前广泛应用的 PLC 控制软件 CODESYS, 设计并封装轨迹规划算法功能库, 通过 ARB1410 机械臂的 D - H 参数配置轴组模型, 模拟机械臂运动控制。仿真结果表明; 改进粒子群算法优化后, 机械臂经全部路径点的总运动时间从 95 缩短至 5.838, 各关节位置曲线平滑无突变, 速度与加速度均在约束范围内; 在优化性能相近的前提下, 较混合 PSO, 改进 PSO 的运行时间从 1.25s 缩短至 0.97s。最后, 使用伟创 AD70 系列伺服电机和驱动器进行伺服实验, 利用 Trace 工具得出的电机运动曲线符合仿真实验数据, 验证了轨迹的平滑性与算法的有效性。 [ABSTRACT FROM AUTHOR] |
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| Database: |
Complementary Index |