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Hybrid Global Optimum Beetle Antennae Search - Genetic Algorithm Based Welding Robot Path Planning

机译:混合全局最优甲壳虫天线搜索-基于遗传算法的焊接机器人路径规划。

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This paper, the welding task of the body-in-white spot welding robot is coordinated, and the welding path optimization algorithm is studied to effectively improve the welding efficiency. The genetic algorithm (GA) is added to each iteration of the Beetle Antennae Search algorithm (BAS), and the advantage of fast convergence of the BAS is used to accelerate the convergence speed of the GA. The mutation mechanism of GA helps BAS solve local optimal situations. Therefore, a hybrid algorithm (BAS-GA) having the advantages of BAS and GA is formed. Then, the Three dimensional welding path planning problem is solved with BAS-GA. In addition, we carried out simulation experiments in the PLM simulation system, and verified the path optimization ability through the test, indicating that BAS-GA has good practicability in the optimization of welding robot path.
机译:本文协调了白车身点焊机器人的焊接任务,研究了焊接路径优化算法,以有效提高焊接效率。将遗传算法(GA)添加到Beetle天线搜索算法(BAS)的每次迭代中,并且利用BAS快速收敛的优势来加快GA的收敛速度。 GA的变异机制有助于BAS解决局部最优情况。因此,形成了具有BAS和GA的优点的混合算法(BAS-GA)。然后,使用BAS-GA解决三维焊接路径规划问题。另外,我们在PLM仿真系统中进行了仿真实验,并通过测试验证了路径优化能力,表明BAS-GA在焊接机器人路径优化中具有良好的实用性。

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