基于曲率优化的机器人砂带磨削轨迹规划

doi:10.13973/j.cnki.robot.170408

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马凯威, 韩良, 孙小肖, 刘平文, 张凯. 基于曲率优化的机器人砂带磨削轨迹规划[J]. 机器人, 2018, 40(3): 360-367.DOI: 10.13973/j.cnki.robot.170408. MA Kaiwei, HAN Liang, SUN Xiaoxiao, LIU Pingwen, ZHANG Kai. Trajectory Planning for Robotic Belt Grinding Based on Curvature Optimization. ROBOT, 2018, 40(3): 360-367. DOI: 10.13973/j.cnki.robot.170408.

摘要针对复杂曲面零件砂带磨削编程效率低、精度差的问题，基于B样条曲线曲面重构和机器人离线编程技术，提出了一种根据关键接触点曲率值生成工业机器人磨削轨迹的方法.首先，利用零件表面上需要进行砂带磨削的关键接触点和积累弦长参数化法构造节点矢量，从而计算出磨削轨迹的B样条基函数；其次，根据控制顶点反求矩阵得到全部未知控制点和3次B样条加工曲线；然后，分析关键接触点之间的曲率变化率和弧长，对关键点细化生成符合磨削工艺要求的目标点；最后，通过求解双3次B样条插值曲面方程获得目标点的加工姿态.以水龙头磨削为例进行试验，结果表明曲率优化算法磨削的零件表面轮廓形状明显优于截面法，且其粗糙度值能稳定在0.082 μm左右，可以有效提高工件表面加工质量.

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	马凯威
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关键词 ：机器人, 砂带磨削, B样条曲线曲面, 轨迹规划, 曲率优化

Abstract：Aiming at the problems of low programming efficiency and machining precision of belt grinding for complex surface parts, a method is proposed to generate a grinding path for industrial robots according to the curvature values of key contact points, based on the reconstructions of B-spline curves and surfaces and the robot off-line programming technique. Firstly, the B-spline basis functions of the grinding trajectory are calculated by the knot vectors constructed with the key contact points on the surfaces of parts for belt grinding and the accumulation chord length parameter method. Secondly, all unknown control points and cubic B-spline machining curves are obtained according to the inverse matrix of the control points. Thirdly, the key points are refined to produce the target points conforming to grinding process requirements by analyzing the curvature variation rate and arc length between key contact points. Finally, the processing postures of the target points are obtained according to the solution of bi-cubic B-spline interpolation surface equations. Test results of faucet grinding show that the curvature optimization algorithm is obviously better than the section method in term of the contour shape of the workpiece surface, and its roughness value can be stabilized at about 0.082 μm, which effectively improve the surface processing quality of workpieces.

Key words： robot belt grinding B-spline curves and surfaces trajectory planning curvature optimization

收稿日期: 2017-07-01 录用日期: 2017-09-12

TP242

基金资助:国家自然科学基金（51275087）；江苏省科技计划（SBE2015000030）；中央高校基本科研业务费专项资金和江苏省普通高校研究生科研创新计划（KYLX16_0187）.

通讯作者: 韩良,melhan@seu.edu.cn E-mail: melhan@seu.edu.cn

作者简介: 马凯威(1990-),男,博士生.研究领域:机器人控制,复杂曲面磨削;
韩良(1967-),男,博士,教授.研究领域:工业机器人,非标自动化;
孙小肖(1989-),男,博士生.研究领域:机器人技术,精密传动,智能控制与运用.

链接本文:

https://robot.sia.cn/CN/10.13973/j.cnki.robot.170408 或 https://robot.sia.cn/CN/Y2018/V40/I3/360

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