基于多策略融合粒子群算法的点焊机器人路径多目标优化

Automatic welding technology is very important for intelligent manufacturing, and welding robot path planning is the key problem of welding automation. In order to realize intelligent path optimization for spot welding robot in welding manufacturing process, factors related to path planning will be analyzed first. Then the multi-objective path planning problem will be modeled based on consideration about the influence factors (path length, obstacle avoidance, energy saving, and multi-robot coordination, etc.). And the improvement of welding efficiency is selected as the main objective here. For improving optimization effects of particle swarm optimization (PSO) algorithm, various optimization strategies will be studied and applied. Discretization of the established hybrid PSO will be conducted for application in spot welding robot path planning. The results of this work have both academic significance and application potential, and would lead to high quality and high efficiency welding. It would improve welding automation level and enterprise economic benefit, and it also conforms to the developing trends of intelligent manufacturing and green manufacturing.

智能制造对焊接自动化程度要求越来越高，焊接机器人的路径规划是焊接自动化关键问题之一。本项目针对焊接加工中的点焊机器人路径多目标智能规划问题，分析与路径规划相关的影响因素。以焊接效率的提高为主要优化目标，综合考虑焊接路径长度、避障、节能、多机器人协调等各种因素，进行多目标路径规划问题分析。研究多种优化策略，进行多策略融合粒子群优化算法研究，对改进的混合粒子群算法进行离散化，以适用于焊接机器人路径优化问题。研究成果对于提高焊接效率、产品质量具有重要理论意义和工程价值，能够有效提高焊接自动化水平以及企业经济效益，更是顺应了绿色制造、智能制造这一制造业发展方向。

对于点焊机器人路径优化问题，结合路径长度、能耗、多机器人协调、避障等多种影响因素，进行了优化问题的描述。开展了基于改进粒子群优化算法的多目标优化算法研究工作，实现了点焊机器人避障策略研究，并开展了双焊接机器人路径优化。在点焊机器人路径优化工作基础上，针对弧焊机器人的不同，进行了焊接变形的有限元分析，为后续弧焊机器人的路径优化奠定了一定的工作基础。