Strategies for Improving Robot Registration Performance

Published

January 26, 2018

Author(s)

Karl Van Wyk, Jeremy A. Marvel

Abstract

The ability to calculate rigid-body transformations between arbitrary coordinate systems (i.e., registration) is an invaluable tool in robotics. This effort builds upon previous work by investigating strategies for improving the registration accuracy between a robotic arm and an extrinsic coordinate system with relatively inexpensive parts and minimal labor. The framework previously presented has been expanded with new test methodology to characterize the effects of strategies to improve registration performance. In addition, statistical analyses of physical trials reveal that leveraging more data and applying machine learning are two major components for significantly reducing registration error. One-shot peg-in-hole tests were conducted to show the application-level performance gains obtained by improving registration accuracy. Trends suggest that the maximum translation positioning error (post-registration) is a good, albeit not perfect, indicator for peg insertion performance.

Citation

IEEE Transactions on Automation Science and Engineering

Volume

15

Issue

1

Pub Type

Journals

Download Paper

https://doi.org/10.1109/TASE.2017.2720478

Keywords

robot registration, robot performance, multi-robot coordination

Citation

Van, K. and Marvel, J. (2018), Strategies for Improving Robot Registration Performance, IEEE Transactions on Automation Science and Engineering, [online], https://doi.org/10.1109/TASE.2017.2720478 (Accessed October 11, 2025)