运动规划
路径(计算)
机器人焊接
机器人
焊接
电弧焊
数学优化
计算机科学
算法
工程类
数学
人工智能
机械工程
程序设计语言
作者
Xin Zhou,Xuewu Wang,Xingsheng Gu
标识
DOI:10.1080/0305215x.2021.2021196
摘要
Multi-objective welding robot path planning is becoming an important problem owing to the developing requirements of industrial production intelligence. An approach with path planning and optimization is proposed for solving the problem of arc welding. A rapidly exploring random tree* (RRT*)-based local path search algorithm is applied to generate a set of collision-free paths between any two welding seams, and the global search algorithm based on the decomposition-based multi-objective evolutionary algorithm (MOEA/D) framework is introduced to improve welding production efficiency by optimizing the requested contradictory objectives, namely, path length, trajectory smoothness and energy consumption. Both proposed algorithms are tested in different instances and on an actual welding workpiece, and the results prove that the proposed method could be useful in industrial production.
科研通智能强力驱动
Strongly Powered by AbleSci AI