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Improving 3D Vision-Robot Registration for Assembly Tasks

Published

Author(s)

Marek Franaszek, Geraldine S. Cheok, Karl Van Wyk, Jeremy A. Marvel

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

Keywords

rigid-body registration, autonomous robotic systems, bias
Created April 3, 2020, Updated June 3, 2020