基于遗传模拟退火算法的弧焊机器人系统协调路径规划

深入地研究了弧焊机器人系统的协调路径规划。从全局的角度用5元组序列描述了焊接路径。设计了评价 焊接路径目标函数:焊接位置函数、焊缝成形质量函数、关节位置函数和运动平稳性函数。以线性加权法为求解 多目标规划的基本思想,把遗传模拟退火算法用于弧焊机器人与变位机协调路径规划,取得了很好的效果。协调 路径规划精确地保证焊缝的最佳焊接位置与最佳的焊枪姿态,并能找到柔顺的焊接路径,提高了机器人焊接的质 量和效率。

Genetic simulated annealing based coordinated path planning for arc welding robot system

The coordinated path planning is lucubrated. At first, the welding path is represented by an array of quintuple. Being the foundation of welding path planning, welding position function, bead forming quality function, joint configuration function and smooth motion function are designed carefully as the objective functions for evaluating the path of the robot welding. Then, the weighted sum approach is used conveniently as the base idea to meet the multi-objective optimization. A genetic simulated annealing algorithm (GSA), which combined the advantages of the genetic algorithms and the simulated annealing algorithm, is employed to plan the coordinated path of robot and positioner for arc welding. Through coordinated path planning, robot can weld the workpiece in the best welding position and the best torch orientation, with smooth motion. Therefore, the coordinated path planning is able to improve the quality and the efficiency of robot arc welding.