Franaszek, M.
, Cheok, G.
, Van, K.
and Marvel, J.
(2020),
Improving 3D Vision-Robot Registration for Assembly Tasks, NIST Interagency/Internal Report (NISTIR), National Institute of Standards and Technology, Gaithersburg, MD, [online], https://doi.org/10.6028/NIST.IR.8300
(Accessed November 23, 2024)
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Improving 3D Vision-Robot Registration for Assembly Tasks
Published
Author(s)
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Abstract
Quality 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). This paper presents a procedure which leads to decreased TRE when the bias is larger than the noise. Experiments performed with a motion tracking system and robot arm show that the Root Mean Squared target errors (RMST) can be reduced by as much as 84 % by placing fiducials in carefully selected locations in the working volume and through the use of the Restoration of Rigid Body Condition (RRBC) method.Citation
NIST Interagency/Internal Report (NISTIR) - 8300
Report Number
8300
NIST Pub Series
Pub Type
NIST Pubs
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Keywords
rigid-body registration, autonomous robotic systems, bias
Citation
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Created April 3, 2020, Updated June 3, 2020