基于改进GA-PSO的核岛建设用支架安装车臂架轨迹规划OA

In order to solve the trajectory planning problem of the bracket mounting vehicle boom in the narrow space of the nuclear island,a control scheme combining improved D-H(Denavit-Hartenberg)modeling,three-dimensional laser positioning and improved genetic algorithm-particle swarm optimization(GA-PSO)algorithm is proposed.Firstly,the improved D-H method was used to establish the kinematic model of the bracket mounting vehicle boom,and the coupled double parallelogram linkage mechanism was equivalent to a moving joint to eliminate the ambiguity of the traditional kinematic modeling.Then,a three-dimensional positioning device consisting of a SICK DT35 laser distance sensor and a two-axis pan-tilt unit was built to realize the millimeter-level pose detection of brackets.At the same time,a multi-objective fitness function(incorporating jerk,energy consumption,smoothness,trajectory deviation and collision penalty)for boom trajectory planning was constructed,and the inertia weight based on dynamic adjustment of iteration times and adaptive mutation strategy were introduced to improve the GA-PSO algorithm.Finally,the improved GA-PSO algorithm was used to optimize the joint space trajectory of the boom under the kinematic constraints,and the optimization performance of the improved GA-PSO,improved PSO and basic PSO algorithms was compared.The results showed that compared with the basic PSO and improved PSO algorithms,the positioning error of the boom end optimized by the improved GA-PSO algorithm was within±1.5 mm,the trajectory satisfied the joint constraints,and there was no collision risk,which met the installation requirements of nuclear island brackets.The research results provide a reference for the trajectory planning of construction machinery arm in complex narrow environments.