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.

中文翻译：

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基于多目标灰狼算法的点焊机器人路径规划

传统点焊的路径规划多采用手工示教方式。在这里，从焊接长度和焊接时间两个方面建立了一种新的路径规划模型。然后提出了一种具有密度估计的多目标灰狼优化算法（DeMOGWO）来解决多目标离散问题。该算法改进了编码方法和运算规则，并在环境更新中设置了密度估计机制。通过与其他五种算法在基准问题上的比较，仿真结果表明，DeMOGWO 在兼顾多样性和收敛性方面具有竞争力。最后利用DeMOGWO算法对建立的路径规划模型进行求解。获得的帕累托解可用于指导白车身 (BIW) 工件的焊接顺序。