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arXiv 2025年

作者： Thoms, Alexander Papalia, Alan Velasquez, Jared Rosen, David M. Narasimhan, Sriram Sensing and Robotics for Infrastructure Laboratory University of California Los Angeles Los Angeles United States The Massachusetts Institute of Technology The MIT-WHOI Joint Program in Oceanography/Applied Ocean Science & Engineering Woods Hole CambridgeMA United States Robust Autonomy Lab Northeastern University BostonMA United States

Reliable simultaneous localization and mapping (SLAM) algorithms are necessary for safety-critical autonomous navigation. In the communication-constrained multi-agent setting, navigation systems increasingly use point-to-point range sensors as they afford measurements with low bandwidth requirements and known data association. The state estimation problem for these systems takes the form of range-aided (RA) SLAM. However, distributed algorithms for solving the RA-SLAM problem lack formal guarantees on the quality of the returned estimate. To this end, we present the first distributed algorithm for RA-SLAM that can efficiently recover certifiably globally optimal solutions. Our algorithm, distributed certifiably correct RA-SLAM (DCORA), achieves this via the Riemannian Staircase method, where computational procedures developed for distributed certifiably correct pose graph optimization are generalized to the RA-SLAM problem. We demonstrate DCORA’s efficacy on real-world multi-agent datasets by achieving absolute trajectory errors comparable to those of a state-of-the-art centralized certifiably correct RA-SLAM algorithm. Additionally, we perform a parametric study on the structure of the RA-SLAM problem using synthetic data, revealing how common parameters affect DCORA’s performance. Copyright © 2025, The Authors. All rights reserved.

关键词： Navigation systems

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