Industrial Robot Optimal Time Trajectory Planning Based on Genetic Algorithm

摘要

In this paper, an optimal trajectory planning method for industrial robots is proposed, which uses a cubic polynomial curve to connect the adjacent path points, so that the joint trajectory curve is more smooth. Taking the six-dof industrial robot of yaskawa as an example, the fitness function and constraint condition function were determined, and the shortest time interval between path points was obtained by using the genetic algorithm toolbox of MATLAB. At the same time, the running time of 6 joints is synchronized between adjacent path points. MATLAB was used to simulate the optimization results and obtain the change curves of kinematics parameters of each joint. The simulation results show that the trajectory curves of each axis are continuous and smooth, and the kinematics parameters meet the constraints, which shortens the trajectory running time, improves the working efficiency, and lays a foundation for robot control.