Trajectory Planning of Manipulators Based on Artificial Immune-improved Particle Swarm Optimization Algorithm
Guo Xin
Li Lijun
Abstract：The trajectory of the welding robot is complex and the control accuracy is high.A trajectory planning method is proposed to meet the multi-objective constraints.Aiming at the requirement of robot trajecto-ry smoothness,the Cartesian space waypoints are parameterized based on the quintic non-uniform rational B-splines(NURBS)curve.Based on the path constraints and operational requirements of industrial robots,three ki-nematic indicators of time,energy consumption,and jump are selected as the objective optimization functions,and artificial immune bimodal particle swarm is used for trajectory optimization.In order to balance the explora-tion and utilization of particles,a bimodal model is added,and an artificial immune system is introduced to in-crease the particle diversity and the later convergence ability.According to the Pareto solution set,the optimal trajectory of each joint of the welding robot satisfying the constraints is obtained,and the effectiveness of the method is proved by Matlab simulation.The results show that the planned trajectory meets the actual engineer-ing requirements.
Keywords：Welding robotQuintic NURBS curvePath planningImmune particle swarm algorithmMulti-objective optimization
Publication Date：2024-05-15
Online Publishing Date：2026-09-12(First online date of this platform, not the publication date of the document)
Pages：8( 33-40 )