Applied Sciences, Vol. 13, Pages 4439: Trajectory Optimization of High-Speed Robotic Positioning with Suppressed Motion Jerk via Improved Chicken Swarm Algorithm

Applied Sciences, Vol. 13, Pages 4439: Trajectory Optimization of High-Speed Robotic Positioning with Suppressed Motion Jerk via Improved Chicken Swarm Algorithm

Applied Sciences doi: 10.3390/app13074439

Authors: Yankun Li Yuyang Lu Dongya Li Minning Zhou Chonghai Xu Xiaozhi Gao Yu Liu

For the trajectory optimization of the time–jerk of robotic arms with a chicken swarm optimization algorithm, using five-order B-spline interpolation can ensure smooth and continuous acceleration, but, due to the performance problems of the algorithm, the low solution accuracy and the slow convergence speed, the ideal trajectory curve cannot be obtained. To address these problems, an improved chicken swarm algorithm based on a parallel strategy and dynamic constraints (PDCSO) is proposed, where the rooster update method is employed with a parallel strategy using X-best guidance and a Levy flight step. Dynamic constraints for the rooster are given, followed by the hens, and the optimal rooster position that improved the convergence accuracy while preventing the local optimum was determined. Simulation experiments using 18 classical test functions showed that the PDCSO algorithm outperformed other comparative algorithms in terms of convergence speed, solution accuracy and solution stability. Simulation validation in ADAMS and real machine tests proved that PDCSO can effectively reduce the running time and motion shock for robotic arms and improve the execution efficiency of such arms.