首页|New Robotics Findings from Southwest Jiaotong University Discussed (A Dual-robot Cooperative Arc Welding Path Planning Algorithm Based On Multi-objective Cross-entropy Optimization)
New Robotics Findings from Southwest Jiaotong University Discussed (A Dual-robot Cooperative Arc Welding Path Planning Algorithm Based On Multi-objective Cross-entropy Optimization)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily NewsNew research on Robotics is the subject of a repo rt. According to news reporting originating from Chengdu, People's Republic of C hina, by NewsRx correspondents, research stated, "In this paper a novel discrete multi-objective cross-entropy optimization (CrMOCEO) algorithm is proposed to s olve the path planning problem of dual-robot cooperative arc welding. We strive to find a low-cost, fast and more efficient solution for robotic welding of larg e complex components." Financial support for this research came from Sichuan Province Science and Techn ology Support Program. Our news editors obtained a quote from the research from Southwest Jiaotong Univ ersity, "Firstly, an optimization model of dualrobot welding path planning is es tablished by considering various variables and constraints in the actual welding process. Then, three strategies are introduced to improve the multiobjective c ross-entropy optimization (MOCEO) algorithm to better solve the discrete path pl anning problem. Finally, in order to verify feasibility and effectiveness of the proposed algorithm, it is used to solve the 2-, 3-, 5-and 7-objective WFG2-9 p roblems and plan some typical welding seams of a large complex component, the MO CEO, NSGA-II, MOPSO and MOGWO are used for comparison. The simulation demonstrat es that the CrMOCEO can obtain better solutions for multiple objectives than the other four algorithms, and the path solved by the CrMOCEO is tested in the Gaze bo physical model and workshop site, the results further verified the effectiven ess of the CrMOCEO algorithm."
ChengduPeople's Republic of ChinaAsiaAlgorithmsEmerging TechnologiesMachine LearningRobotRoboticsSouthwe st Jiaotong University
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