Experimentally registering position sensors

Everett, Louis J.; Burnett, Mahrya

doi:10.1109/robot.1996.503847

Cited by 4 publications

(2 citation statements)

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“…If each error term caused by the offset is considered as a fixed value (e.g. dX mbase and dX 0 sbase ), then the placement error is errX inc , as shown in equation (11) errX inc = dX mbase À dX 0 sbase = Y inc Á u inc = dx mbase dy mbase À cos a À sin a dx rot sin a cos a dy rot Y inc and u inc are the regressor matrix and parameter matrix of the incomplete error model, respectively, as shown in equation (12) Y inc Á u inc = 1 À cos a 0 sin a 0 À sin a 1 À cos a dx mbase À dx rot dx sbase À dx rot dy mbase À dy rot dy sbase À dy rot …”

Section: Incomplete Error Model Based On Hand-eye Calibration Errormentioning

confidence: 99%

“…Obtaining the unique solution of the equation necessitates the inclusion of specific constraints during the calibration process. 11,12 For example, the robots must perform three mutually orthogonal translations. 13 Zhuang proposed a hand–eye calibration method for the Selective Compliance Assembly Robot Arm (SCARA) robot with 4 degrees of freedom (DOFs).…”

Section: Introductionmentioning

confidence: 99%

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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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Section: Incomplete Error Model Based On Hand-eye Calibration Errormentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%