摘要
该文以工业自动化中的5R工业机器人为研究对象,在关节空间中采用3-5-3样条插值曲线建立起轨迹基元函数,并提出一种改进遗传算法(genetic algorithm,GA)对3-5-3样条插值曲线的各段插值时间分别进行优化用以满足不同速度的约束条件。在遗传算法中采用轮盘赌法和锦标赛选择法相结合的选择算子并针对交叉概率和变异概率分别设置自适应参数调节机制,以实现算法性能的提升,防止种群陷入局部极值。在MATLAB中搭建5R机器人仿真平台进行实时实验,得到了各关节角度位置、角速度、角加速度、急动度曲线,实验表明该方法能够有效实现不同速度约束下的最优时间轨迹规划。
This paper focuses on the 5R industrial robot in industrial automation,uses the 3-5-3 spline interpolation curve to establish the trajectory primitive function in the joint space,and proposes an improved genetic algorithm(GA)to optimize the interpolation time of each segment of the 3-5-3 spline interpolation curve respectively to meet the constraints of different speeds.We adopted a selection operator that combines the roulette selection and the tournament selection in the genetic algorithm,and set adaptive parameter adjustment mechanisms for the crossover probability and mutation probability respectively,which can improve the performance of the algorithm and prevent the population from falling into local extreme.We built a 5R robot simulation platform in MATLAB to conduct real-time experiments,and obtained the angular position,angular speed,angular acceleration,and jerk curves of each joint.The experiments show that this method can realize the optimal time trajectory planning effectively under different speed constraints.
作者
周琪钧
李国洪
吴金泽
ZHOU Qi-jun;LI Guo-hong;WU Jin-ze(Tianjin Key Laboratory of Control Theory&Applications in Complicated System,Tianjin University of Technology,Tianjin 300384,China)
出处
《自动化与仪表》
2022年第8期47-53,57,共8页
Automation & Instrumentation
基金
国家重点研发计划项目(2017YFB1303304)
天津市科委重点研发计划项目(18YFFCTG00040)。
关键词
工业机器人
轨迹规划
遗传算法
速度约束
最优时间
industrial robot
trajectory planning
genetic algorithm(GA)
speed constrains
time optimal
