Validation and mathematical model of workspace Measuring and Positioning System as an integrated metrology system for improving industrial robot positioning

Xue, Bin; Zhu, Jigui; Zhao, Ziyue; Wu, Jun; Liu, Zhexu; Wang, Qiong

doi:10.1177/0954405413499901

Cited by 14 publications

(10 citation statements)

References 49 publications

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“…The results obtained for Strategy 3 show that even if the registration is poor, small target registration error is achievable if the target location is corrected by the RRBC method. A similar conclusion was drawn in [23] where inaccurate registration was compensated by a series of corrections leading to an acceptable level of the final error. The main difference between the enhanced RRBC method and the iterative method used in [23] is that RRBC modifies only one, final commanded point.…”

Section: Discussionsupporting

confidence: 70%

“…Unlike the RRBC or VEC techniques or the method introduced in [12] which only modify the location of the final destination point, visual servoing is an iterative process which constantly modifies robot trajectory. Successful application of such iterative procedure was demonstrated by Xue et al on industrial robot by reducing absolute error to less than 0.2 mm [23]. Other, non-visual servoing strategies have also been developed for assembly applications.…”

Section: Related Workmentioning

confidence: 99%

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Improving 3D vision-robot registration for assembly tasks

Franaszek¹,

Cheok²,

Wyk³

et al. 2020

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Good registration between the coordinate frames of a perception system and a robot is important for the efficient operation of autonomous systems in vision-guided assembly lines. Rigid-body registration, which is based on the measurement of corresponding points (fiducials) in both frames, is a commonly used method. Noise and possible bias in the measured points degrade the quality of registration as gauged by the Target Registration Error (TRE). A method to restore the rigid body condition (RRBC) was recently developed to reduce TRE when the bias is larger than the noise. This was achieved by applying corrections to target locations in the vision sensor frame. This paper presents two procedures to improve the performance of the RRBC method by: 1) selecting the location of fiducials used for calculating correction to the target location and 2) selecting the correct arm configuration for fiducial from multiple configurations as calculated by inverse kinematics. Experiments performed with a motion tracking system and two different robot arms show that these two procedures can further reduce the Root Mean Square of TRE (RMST) to less than 20 % of the uncorrected RMST.

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Section: Discussionsupporting

confidence: 70%

Section: Related Workmentioning

confidence: 99%

Improving 3D vision-robot registration for assembly tasks

Franaszek¹,

Cheok²,

Wyk³

et al. 2020

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“…2 Machine vision can be used to assist the automatic stiffener bonders (ASBs) in precise positioning in order to achieve high-speed, precision bonding; however, this approach requires calibration to eliminate errors. [3][4][5] First, laser interferometers, step gauges, and double ballbars are commonly used to measure and calibrate geometrical errors in motion mechanisms, in order to enhance precision in control. [6][7][8][9][10] Second, hand-eye calibration is also required to rectify errors in the transformation between coordinate systems, which is equivalent to solving matrix equations of the form AX = XB.…”

Section: Introductionmentioning

confidence: 99%

Vision-based calibration/compensation technique for automatic stiffener bonder

Xie

et al. 2016

Proceedings of the Institution of Mechanical Engineers, Part B:

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This study developed a novel error compensation method aimed at eliminating placement error caused by hand-eye calibration and pick-and-place tool motions in automatic stiffener bonder for flexible printed circuit. Using the transformation of homogeneous coordinates to develop an error model of the system describing the coupling of errors among various coordinate systems, the least squares method is used to calculate the unknown model parameters. The experiment results demonstrate that this error compensation method reduced placement error by an order of magnitude. The mounting precision throughout the entire work area was 60.046 mm at 3sigma, and for flexible printed circuit products with a specification limit of 0.1 mm, the process capability index of the automatic stiffener bonder in this study was 2.19. This represents that the system is capable of fully satisfying the precision requirements of flexible printed circuit stiffener bonding. The proposed system employing a vibrating feeder bowl and machine vision-aided target positioning is applicable to a variety of stiffeners, which enhances production flexibility. The proposed error model considers the complex coupling effect of the errors among multiple coordinate systems in hand-eye calibration, without the need of detecting and calculating the calibration error item by item, and takes into account the errors produced by the rotation and downward pressing motions of the pick-and-place tool.

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“…1,2 Among these coordinate measurement instruments, the wMPS, the workspace measurement and positioning system, is a large-scale distributed system for the measurement of three-dimensional (3-D) coordinates based on the intersection of rotating laser planes from multistations. [4][5][6][7] The components of the wMPS are a network of transmitters, preprocessors, a terminal computer, and a number of receivers. [4][5][6][7] The components of the wMPS are a network of transmitters, preprocessors, a terminal computer, and a number of receivers.…”

Section: Introductionmentioning

confidence: 99%

Transmitter parameter calibration of the workspace measurement and positioning system by using precise three-dimensional coordinate control network

et al. 2014

Self Cite

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The workspace measurement and positioning system is a three-dimensional (3-D) coordinate system based on laser scanning, which is widely applied in large-scale metrology. As a core part ensuring measurement accuracy, the transmitter parameters' calibration is the critical technique of the system. The present transmitter parameter calibration method relies on auxiliary measurement equipment, which is more error prone and less efficient. This paper will focus on the improvement of the transmitter parameters' calibration by using a highly precise 3-D coordinate control network. Several calibration points with known coordinates are set in the workspace to establish the precise 3-D coordinate control network. After the new model of transmitter parameter calibration has been explained, both the calculation method for optimization and the production of the initial iteration value are given. As indicated by the results of the verifying experiment, the accuracy and efficiency of the transmitter calibration can be distinctly improved by using the proposed method. The experimental data show that the 3-D coordinate measurement error has obviously decreased from 0.3 to 0.15 mm as a merit of the proposed method.

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Validation and mathematical model of workspace Measuring and Positioning System as an integrated metrology system for improving industrial robot positioning

Cited by 14 publications

References 49 publications

Improving 3D vision-robot registration for assembly tasks

Improving 3D vision-robot registration for assembly tasks

Vision-based calibration/compensation technique for automatic stiffener bonder

Transmitter parameter calibration of the workspace measurement and positioning system by using precise three-dimensional coordinate control network

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