Affiliations: [a] School of Information Science and Engineering, Wuhan University of Science and Technology, Wuhan, China
| [b] Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education, Wuhan, China
| [c] School of Management, Wuhan University of Science and Technology, Wuhan, China
Correspondence:
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Corresponding author. Yuntao Zhao, School of Information Science and Engineering, Wuhan University of Science and Technology. No. 947, Heping Road, Qingshan District, Wuhan, Hubei, 430081, China. E-mail: [email protected].
Abstract: The path planning of traditional spot welding mostly uses manual teaching method. Here, a new model of path planning is established from two aspects of welding length and welding time. Then a multi-objective grey wolf optimization algorithm with density estimation (DeMOGWO) is proposed to solve multi-object discrete problems. The algorithm improves the coding method and operation rules, and sets the density estimation mechanism in the environment update. By comparing with other five algorithms on the benchmark problem, the simulation results show that DeMOGWO is competitive which takes into account both diversity and convergence. Finally, the DeMOGWO algorithm is used to solve the model established of path planning. The Pareto solution obtained can be used to guide the welding sequence of body-in-white(BIW) workpieces.
Keywords: Spot welding robot, multi-objective grey wolf optimization algorithm, density estimation, path planning
