基于知识和改进PRM算法的钣金折弯机器人路径自动规划与优化  

Automatic Path Planning and Optimization of Sheet Metal Bending Robot Based on Knowledge and Improved PRM Algorithm

作　　者：纪广东 游有鹏[1] 王鹏宇 钱爽 JI Guangdong;YOU Youpeng;WANG Pengyu;QIAN Shuang(College of Mechanical Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China;Shanghai Xinyuelianhui Electronic Technology Co.,Ltd.,Shanghai 200233,China)

机构地区：[1]南京航空航天大学机电学院,江苏南京210016 [2]上海新跃联汇电子科技有限公司,上海200233

出　　处：《机械与电子》2024年第6期38-44,49,共8页Machinery & Electronics

基　　金：国家重点研发计划资助项目(2018YFB1309203)。

摘　　要：针对钣金折弯机器人离线编程仿真过程中的任务单元间运动规划问题,提出了一种基于经验知识的初始路径节点生成方法。基于初始路径节点作为体心来构建采样模型,通过获取模型顶点和体心作为采样点来改进原始PRM算法采样方式。通过多次迭代构建采样模型,使得该算法路径具有了渐进最优性,从而实现了钣金折弯机器人路径自动规划与优化。最后,通过钣金折弯机器人的仿真实验,验证了该算法的可行性与高效性。An initial path node generation method based on empirical knowledge is proposed for the inter-task cell motion planning problem during offline programming simulation of sheet metal bending robots.The sampling model is constructed based on the initial path nodes as body centres,and the sampling method of the original PRM algorithm is improved by obtaining model vertices and body centres as sampling points.By constructing the sampling model through several iterations,the algorithm path has asymptotic optimality,achieving automatic planning and optimization of the path of the sheet metal bending robot.Finally,the feasibility and efficiency of the algorithm are verified by the simulation experiment of the sheet metal bending robot.

关 键 词：折弯机器人 路径规划 经验知识 PRM算法 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置] TP391.1[自动化与计算机技术—控制科学与工程]