Application of an Improved Particle Swarm Optimization Algorithm in the Robotic Arm of a Handling Robot
Zhang Zhenhe
Yang Daoyu
Shu Yibin
Liu Jiangyi
Cao Jingyi
Chen Meirong
Abstract：Aiming at the time optimization problem of the space planning of the handling robot,an im-proved particle swarm optimization(PSO)with dynamic learning factor,variable inertia weight factor and beetle antennae search(BAS)algorithm is proposed.The workspace is obtained by the kinematics analysis.The 3-5-3 polynomial interpolation is introduced for trajectory planning.The acceleration and velocity of the moving pro-cess are restrained,and the shortest time of the moving process is obtained.The convergence speed of the im-proved PSO is compared,and the movement time of each joint is analyzed and then verified by simulation and experiment.The learning factor is set as a variable to make the algorithm jump out of local optimum.The vari-able inertia weight factor improves the search efficiency.Combined with the BAS algorithm,the speed and preci-sion of the search algorithm are improved.The results show that the convergence speed and accuracy of the im-proved PSO algorithm are improved,the local optimality is avoided,and the overall motion time is reduced by about 15.9％.The joint angle,velocity and acceleration curves of the robotic arm are smooth and stable,and the improved algorithm is effective.
Keywords：Robotic armTime optimizationPSO algorithmVariable inertia weight factorBeetle antennae search algorithm
Publication Date：2024-08-15
Online Publishing Date：2026-09-12(First online date of this platform, not the publication date of the document)
Pages：8( 49-56 )