基于五次B样条的工业机器人轨迹优化
Trajectory Optimization of Industrial Robots Based on Quintic B-Splines
宋辉 1李东辉1
作者信息
- 1. 沈阳工业大学信息科学与工程学院,沈阳 110870
- 折叠
摘要
为提高工业机器人的工作效率,提出一种以时间最优为目标的轨迹优化方法,在5次B样条曲线轨迹规划原理的基础上,引入遗传算法对轨迹进行优化.针对工作时间建立适应度函数,并通过选择交叉概率和变异概率操作产生新的轨迹解,与未被淘汰的父代组成新的种群,经过迭代求得运行时间最优的期望解.利用MATLAB软件对这一方法进行仿真,结果表明,经分析遗传算法优化后,轨迹运行时间明显减少,且具有良好的轨迹效果.
Abstract
To improve the working efficiency of industrial robots,a trajectory optimization method with minimum time as the objective is proposed.Based on the principle of quintic B-spline curve trajectory planning,a genetic algorithm is introduced to optimize the trajectory.A fitness function is established for the working time,and new trajectory solutions are generated by selecting crossover probability and mutation probability operations,and they are combined with the uneliminated parent generation to form a new population.The optimal expected solution with the shortest running time is obtained through iteration.The method is simulated using MATLAB software,and the results show that after analysis of genetic algorithm optimization,the trajectory running time is significantly reduced and the trajectory effect is good.
关键词
轨迹规划/5次B样条曲线/轨迹优化/遗传算法Key words
Trajectory planning/Quintic B-spline curve/Trajectory optimization/Genetic algorithm引用本文复制引用
出版年
2024
NETL
NSTL
万方数据