Multi-Agent 3D Map Reconstruction and Change Detection in Microgravity with Free-Flying Robots
Abstract
Assistive free-flyer robots autonomously caring for future crewed outposts -- such as NASA's Astrobee robots on the International Space Station (ISS) -- must be able to detect day-to-day interior changes to track inventory, detect and diagnose faults, and monitor the outpost status. This work presents a framework for multi-agent cooperative mapping and change detection to enable robotic maintenance of space outposts. One agent is used to reconstruct a 3D model of the environment from sequences of images and corresponding depth information. Another agent is used to periodically scan the environment for inconsistencies against the 3D model. Change detection is validated after completing the surveys using real image and pose data collected by Astrobee robots in a ground testing environment and from microgravity aboard the ISS. This work outlines the objectives, requirements, and algorithmic modules for the multi-agent reconstruction system, including recommendations for its use by assistive free-flyers aboard future microgravity outposts.
Keywords
Cite
@article{arxiv.2311.02558,
title = {Multi-Agent 3D Map Reconstruction and Change Detection in Microgravity with Free-Flying Robots},
author = {Holly Dinkel and Julia Di and Jamie Santos and Keenan Albee and Paulo Borges and Marina Moreira and Oleg Alexandrov and Brian Coltin and Trey Smith},
journal= {arXiv preprint arXiv:2311.02558},
year = {2024}
}
Comments
11 pages, 8 figures, Manuscript presented at the 74th International Astronautical Congress, IAC 2023, Baku, Azerbaijan, 2 - 6 October 2023. Video presentation: [https://www.youtube.com/watch?v=VfjV-zwFEtU]. Code: [https://github.com/hollydinkel/astrobeecd]