文献类型：期刊文献

英文题名：Dual-Objective Collision-Free Path Optimization of Arc Welding Robot

作者：Wang, Xuewu[1];Wei, Jianbin[1];Zhou, Xin[1];Xia, Zelong[1];Gu, Xingsheng[1]

机构：[1]East China Univ Sci & Technol, Key Lab Smart Mfg Energy Chem Proc, Minist Educ, Shanghai 200237, Peoples R China

年份：2021

卷号：6

期号：4

起止页码：6353

外文期刊名：IEEE ROBOTICS AND AUTOMATION LETTERS

收录：;EI(收录号：20213010690862);WOS:【SCI-EXPANDED(收录号:WOS:000675205800010)】；

基金：This work was supported by the National Natural Science Foundation of China under Grants 62076095 and 61973120.

语种：英文

外文关键词：Dual-objective optimization; arc welding robot; path planning; grid method and obstacle avoidance

摘要：In order to solve the dual-objective path optimization problem of arc welding robot, a complete and novel methodology is proposed, including modeling, collision-free path search and global path optimization. First of all, the grid method is utilized to accurately model the welding workpieces and surrounding environment. Afterwards, an adaptive extension bidirectional RRT* algorithm (AB-RRT*) is used to search for collision-free paths between any two weld seams. Finally, aiming to minimize path length and energy consumption, the global path is optimized through the improved discrete NSGA-III algorithm (IDNSGA-III). Simulation results show that the AB-RRT* algorithm can search for optimal or sub-optimal solutions with higher efficiency. The IDNSGA-III algorithm can properly maintain the trade-off between convergence and distribution. Furthermore, it can obtain satisfactory solutions in a shorter time and provide effective guidance and help for engineers to plan the actual path.