期刊文献+

基于改进麻雀算法的打磨机器臂轨迹优化

Trajectory Optimization of Grinding Machine Arm Based on Improved Sparrow Algorithm
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摘要 为提高打磨机械臂工作效率和减小冲击,提出了一种自适应变异麻雀算法(AMSSA)的轨迹优化方法,使用5次非均匀B样条(NURBS)曲线为打磨轨迹,以工业机器人的运行时间和轨迹平滑性为目标建立目标函数,目标函数通过加权方式归一化,从而得到期望解。仿真结果表明:运行时间减少了24.6%,有效提升了机械臂运行效率和平稳性,该优化方法对于工业机器人在打磨行业的应用具有可行性。 In order to improve the working efficiency of the grinding manipulator and reduce the impact,an adaptive mutation sparrow algorithm(AMSSA)trajectory optimization method is proposed,which uses 5-degree non-uniform B-spline(NURBS)curve as the grinding trajectory,and establishes an objective function aiming at the running time and trajectory smoothness of the industrial robot,and the objective function is normalized by weighting to obtain the expected solution.The simulation results show that the running time is reduced by 24.6%,and the operating efficiency and stability of the manipulator are effectively improved.The optimization method is feasible for industrial robots in the grinding industry.
作者 周康渠 谢茂士 何文杰 ZHOU Kangqu;XIE Maoshi;HE Wenjie(School of Mechanical Engineering,Chongqing University of Technology,Chongqing 400054,China)
出处 《机械工程师》 2024年第7期1-4,共4页 Mechanical Engineer
基金 重庆市技术创新与应用示范重点示范项目“大扭矩轻量化商用车变速箱智能制造车间应用示范项目”(cstc2018jszx-cyzdX0169)。
关键词 打磨机械臂 轨迹优化 NURBS曲线 自适应变异麻雀算法 grinding manipulator track optimization NURBS curves adaptive mutation sparrow algorithm
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