工业机器人多目标轨迹优化

Multi-objective Trajectory Optimization of Industrial Robots

基于工业机器人时间、能量、冲击最优等多目标下的轨迹优化问题,采用多目标优化方法进行研究。采用七次B样条插值曲线,构造工业机器人连续并且两端端点的参数都可以进行设定的轨迹,保证了工业机器人的运动性能。然后采用改进遗传算法对工业机器人进行优化,得出Pareto最优解集。在自主研发的六自由度工业机器人上的仿真结果表明:七次B样条插值可以得到连续的机器人轨迹,改进的遗传算法可使B样条轨迹进行有效的多目标寻优,获得良好的Pareto前沿。

Based on the trajectory optimization problem of industrial robots under multi-objectives such as time,energy,and impact optimization,a multi-objective optimization method was used for research.The seven B-spline interpolation curve was adopted to construct the continuous trajectory of the industrial robot and the parameters at both ends could be set,which ensured the motion performance of the industrial robot.Then an improved genetic algorithm was used to optimize the industrial robot,and the result was Pareto's optimal solution set.The simulation results on a self-developed 6-DOF industrial robot show that the seven B-spline interpolation can be used to get continuous robot trajectory,and the improved genetic algorithm can make the B-spline trajectory perform effective multi-object optimization,then a good Pareto frontier is obtained.