Motion trajectory planning for industrial robots based on BAS-IPSO
YAO Jiangyun
WANG Kuantian
LIU Bin
CHEN Guoqing
Abstract：[Objective]To address the mutual constraint between assembly efficiency and assembly quality of robots in complex assembly scenarios,a beetle antennae search(BAS)strategy was combined with the particle swarm optimization(PSO)algorithm,and an optimal trajectory planning method based on the BAS-improved particle swarm optimization(BAS-IPSO)algorithm was proposed.[Methods]Firstly,a trajectory planning model was established using the 4-5-4 polynomial interpolation method,and an objective function was constructed with time-pulsating impact optimality as the criterion.Secondly,the traditional PSO algorithm was improved by combining a dynamic learning factor with adaptive weight,which overcome the drawbacks of PSO algorithm such as being prone to local optima and slow convergence speed.Finally,the BAS strategy was integrated with the IPSO algorithm to enhance the parallel computing capability of global search and local search.[Results]The results show that,compared with the original algorithm,the proposed BAS-IPSO algorithm reduces the average running time and impact of each joint by 26.5%and 24.2%,respectively.This demonstrates the effectiveness and superiority of the proposed algorithm in the motion control of assembly robots.
Keywords：Assembly robotTrajectory planningTime-pulse impact optimumParticle swarm optimization algorithmBeetle antennae search strategy
Publication Date：2026-05-31
Online Publishing Date：2026-09-12(First online date of this platform, not the publication date of the document)
Pages：7( 163-169 )