[1]王逸潇,俞桂英,丁 烨,等.轮毂曲面机器人力控磨抛路径规划方法[J].机械与电子,2021,(04):70-75.
　WANG Yixiao,YU Guiying,DING Ye,et al.Path Planning for Force-controlled Robotic Grinding of Hub Surfaces[J].Machinery & Electronics,2021,(04):70-75.
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轮毂曲面机器人力控磨抛路径规划方法()
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机械与电子[ISSN:1001-2257/CN:52-1052/TH]

卷:
期数:
2021年04期
页码:
70-75
栏目:
智能工程
出版日期:
2021-04-24

文章信息/Info

Title:
Path Planning for Force-controlled Robotic Grinding of Hub Surfaces
文章编号:
1001-2257（2021）04-0070-06
作者:
王逸潇1; 俞桂英2; 丁 烨1; 郑建明2
1.上海交通大学机械与动力工程学院,上海 200240;
2.浙江万丰科技开发股份有限公司,浙江 嵊州 312400
Author(s):
WANG Yixiao1; YU Guiying2; DING Ye1; ZHENG Jianming2
1.School of Mechanical Engineering， Shanghai Jiao Tong University， Shanghai 200240，China;
2. Zhejiang Wanfeng Technology Development Co., Ltd., Shengzhou 312400， China
关键词:
轮毂磨抛; 曲面分割; 接触力模型; 驻留时间规划; 路径间距规划; 间隔移动规划
Keywords:
hub grinding; surface segmentation; contact force model; residence time planning; path spacing planning; interval movement planning
分类号:
TP242.2;TG580.692
文献标志码:
A
摘要:
针对复杂轮毂曲面的机器人力控磨抛问题，根据预设的平行扫掠线模式进行曲面分割。在各子曲面，根据接触力及材料去除数值模型，构建以磨抛总量最大及残余磨抛量最小为目标的约束非线性优化问题，进而规划各路径离散点的驻留时间及相邻平行路径间距。通过解决非线性整数规划问题，对磨抛工具在子曲面间的抬降进行规划。实验结果表明，该算法能够规划出全覆盖磨抛路径，磨抛量达到预期，残余磨抛量较为平均，磨抛效率较高。
Abstract:
Aiming at force-controlled grinding problems of automobile hubs, we segment the complex surface based on predetermined sweeping line mode. On each sub-surface, we establish the constrained nonlinear optimization problem with goals of maximizing the grinding volume and minimizing the residual grinding volume according to the numerical model of contact force and material removal volume, and then plan the residence time of discrete points in each path and the distance between two adjacent parallel paths. The lifting and lowering of the grinding tool between the sub-surfaces are optimized by solving the nonlinear integer optimization problem. Experiments show that proposed algorithm can generate a full coverage grinding path. At the same time, the grinding amount can reach our expectation, the residual grinding amount is relatively average, and the grinding efficiency is high.

参考文献/References:

[1] ZHU D, FENG X, XU X, et al. Robotic grinding of complex components: A step towards efficient and intelligent machining–challenges, solutions, and applications[J]. Robotics and computer-integrated manufacturing, 2020, 65: 101908.

[2] 王敏. 基于视觉和力反馈的机器人磨抛作业系统研究[D].杭州：浙江大学,2019.

[3] WANG X, ZHANG X, REN X, et al. Point cloud 3D parent surface reconstruction and weld seam feature extraction for robotic grinding path planning[J]. The international journal of advanced manufacturing technology, 2020, 107(1): 827-841.

[4] 张耀. 机器人磨抛轮毂离线编程的研究[D].上海：东华大学,2018.

[5] CHEN X. 5-axis coverage path planning with deep reinforcement learning and fast parallel collision detection[D].Atlanta：Georgia Institute of Technology, 2020.

[6] JIN J. Optimal field coverage path planning on 2D and 3D surfaces[D].Ames：Iowa State University, 2009.

[7] PEREZ-IMAZ H I, REZECK P A, MACHARET D G, et al. Multi-robot 3D coverage path planning for first responders teams[C]//2016 IEEE International Conference on Automation Science and Engineering (CASE). IEEE，2016：1374-1379.

[8] CHOSET H. Coverage of known spaces: The boustrophedon cellular decomposition[J]. Autonomous robots, 2000, 9(3): 247-253.

[9] ACAR E U, CHOSET H, RIZZI A A, et al. Morse decompositions for coverage tasks[J]. The international journal of robotics research, 2002, 21(4): 331-344.

[10] XIONG Y, PARK S I, PADMANATHAN S, et al. Process planning for adaptive contour parallel toolpath in additive manufacturing with variable bead width[J]. The international journal of advanced manufacturing technology, 2019, 105(10): 4159-4170.

[11] HUANG N D , JIN Y Q , LU Y, et al. Spiral toolpath generation method for pocket machining[J]. Computers and industrial engineering, 2019, 139: 106142.

[12] CHEN S S, FAI C C, ZHANG F H, et al. Theoretical and experimental investigation of a tool path control strategy for uniform surface generation in ultra-precision grinding[J]. The international journal of advanced manufacturing technology, 2019, 103: 4307-4315.

[13] LI L, ZHANG Y F , LI H Y , et al. Generating tool-path with smooth posture change for five-axis sculptured surface machining based on cutter’s accessibility map[J]. The international journal of advanced manufacturing technology, 2011, 53(5): 699-709.

[14] WALSHAW C. A multilevel lin-kernighan-helsgaun algorithm for the travelling salesman problem[R]. London:University of Greenwich, 2001.

[15] XIAO M B , DING Y, FANG Z, et al. Contact force modeling and analysis for robotic tilted-disc polishing of freeform workpieces[J]. Precision engineering, 2020,66:188-200.

[16] DEEP K, SINGH K P, KANSAL M L, et al. A real coded genetic algorithm for solving integer and mixed integer optimization problems[J]. Applied mathematics and computation, 2009, 212(2): 505-518.

备注/Memo

备注/Memo:

收稿日期: 2020-12-12

基金项目:国家重点研发计划资助项目（2018YFB1308900）

作者简介：王逸潇（1996—），男，浙江绍兴人，硕士研究生，研究方向为机器人技术；俞桂英（1978—），女，浙江嵊州人，高级工程师，研究方向为机器人应用技术；丁 烨（1982—），男，江苏丹阳人，博士，教授，博士研究生导师，研究方向为机器人学与智能加工技术,通信作者；郑建明（1964—），男，湖北黄冈人，博士，教授，研究方向为机器人、机器视觉与人工智能、3D打印技术。

更新日期/Last Update: 2021-04-16