Robot base frame calibration with a 2D vision system for mobile robotic drilling

被引:1
|
作者
Biao Mei
Weidong Zhu
Kangzheng Yuan
Yinglin Ke
机构
[1] Zhejiang University,The State Key Lab of Fluid Power Transmission and Control, Department of Mechanical Engineering
关键词
Mobile robotic drilling; Robot base frame calibration; 2D vision system; Iterative measurement; Depth control with autofocus; Least-squares fitting;
D O I
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中图分类号
学科分类号
摘要
Mobile robotic drilling for flight control surface assembly at multiple stations demands high positioning accuracy of the equipped industrial robot. However, disturbances, arising from movement from station to station, significantly deteriorate the positioning accuracy. This paper proposes a novel in-process robot base frame calibration method with a 2D vision system. A proposal layout of flight control surface assembly, the developed mobile robotic drilling system, and the 2D vision system are first introduced. Then an iterative measurement scheme is proposed to eliminate measurement errors induced by non-perpendicularity and erroneous object distance during 2D vision-based positioning of preset reference holes. In order to obtain the third-dimension Cartesian coordinates of the reference holes, depth control with autofocus is achieved by using a new sharpness function. Based on the acquired Cartesian coordinates of the reference holes in the robot base frame, and their counterparts measured in advance in the world coordinate system, the description of the robot base frame with respect to the world coordinate system can be obtained with least-squares fitting. Numerical experiments show that depth control with autofocus contributes to enhanced accuracy of robot base frame calibration. Experiments performed on the developed mobile drilling system indicate that the maximum positioning error is about 0.6 mm with the proposed calibration method. Since position errors of drilled fastener holes will be further measured and compensated for based on the 2D vision system, the proposed in-process robot base frame calibration method is effective.
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收藏
页码:1903 / 1917
页数:14
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