Trajectory Optimization of Industrial Robots Based on Quintic B-Splines
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.
NETL
NSTL
万方数据
