机械臂时间-冲击最优轨迹规划
Time-Jerk-Optimal trajectory planning for robot manipulator
王鑫亮 1冯迎宾1
作者信息
- 1. 沈阳理工大学自动化与电气工程学院,辽宁沈阳 110159
- 折叠
摘要
为了提高机械臂的工作效率,减少运动过程中的冲击,提出了一种基于多目标粒子群优化算法的时间-冲击最优轨迹规划方法.针对机械臂的位置以及各阶导数曲线不连续问题,采用5次B样条曲线构造插值轨迹,以保证速度、加速度以及加加速度光滑连续.采用惩罚函数法将带约束的优化问题转化为无约束问题,减少算法的计算时间.为了产生分布良好的Pareto最优边界,通过计算解集间聚集密度的方法保持Pareto最优边界良好的分布性.得到分布均匀的Pareto解集后,将两个目标分别采用最大最小归一化的方法消除在解的选取时由于量纲不同所带来的影响.最后通过仿真验证所提出方法的准确性,为机械臂轨迹优化提供理论参考.
Abstract
In order to improve the efficiency of the robot manipulator and reduce the jerk during its movement,a time-jerk opti-mal trajectory planning method based on a MOPSO(Multi-Objective Particle Swarm Optimization)algorithm is proposed.Aiming at the discontinuity problem of the position,velocity,acceleration and jerk of each joint,the interpolation trajectory is constructed by quintic B-spline functions.The penalty function method is used to transform the optimization problem with constraints into an unconstrained problem,reducing the computation time of the algorithm.The Pareto fronts is kept well-distributed by calculating the aggregation density between solution sets.After obtaining the uniformly distributed Pareto solution set,the maximum-minimum normalization method is applied to each of the two objectives to eliminate the effects of different dimensions in the selection of solutions.Finally,the accuracy of the pro-posed method is verified by simulation,which provides a theoretical reference for the trajectory optimization of the robot manipulator.
关键词
B样条/多目标粒子群优化算法/轨迹规划/轨迹优化/Pareto最优解Key words
B-spline/MOPSO/Trajectory planning/Trajectory optimization/Pareto optimum solution引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据