SCORE: A Second-Order Conic Initialization for Range-Aided SLAM
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2210.03177.pdf
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Author(s)
Papalia, Alan
Morales, Joseph
Doherty, Kevin J.
Rosen, David M.
Leonard, John J.
Date Issued
May 29, 2023
Journal
2023 IEEE International Conference on Robotics and Automation (ICRA)
Publisher
IEEE
Citation
A. Papalia, J. Morales, K. J. Doherty, D. M. Rosen and J. J. Leonard, "SCORE: A Second-Order Conic Initialization for Range-Aided SLAM," 2023 IEEE International Conference on Robotics and Automation (ICRA), London, United Kingdom, 2023, pp. 10637-10644.
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Author's final manuscript
Abstract
We present a novel initialization technique for the range-aided simultaneous localization and mapping (RASLAM) problem. In RA-SLAM we consider measurements of point-to-point distances in addition to measurements of rigid transformations to landmark or pose variables. Standard formulations of RA-SLAM approach the problem as nonconvex optimization, which requires a good initialization to obtain quality results. The initialization technique proposed here relaxes the RA-SLAM problem to a convex problem which is then solved to determine an initialization for the original, non-convex problem. The relaxation is a second-order cone program (SOCP), which is derived from a quadratically constrained quadratic program (QCQP) formulation of the RASLAM problem. As a SOCP, the method is highly scalable. We name this relaxation Second-order COnic RElaxation for RASLAM (SCORE). To our knowledge, this work represents the first convex relaxation for RA-SLAM. We present real-world and simulated experiments which show SCORE initialization permits the efficient recovery of quality solutions for a variety of challenging single- and multi-robot RA-SLAM problems with thousands of poses and range measurements.
Description
2023 IEEE International Conference on Robotics and Automation (ICRA 2023)
May 29 - June 2, 2023. London, UK
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Creative Commons Attribution-Noncommercial-ShareAlike
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DOI of Published Version
https://doi.org/10.1109/icra48891.2023.10160787
