Multi-Agent 3D Map Reconstruction and Change Detection in Microgravity with Free-Flying Robots
This work addresses the need for autonomous monitoring and fault detection in microgravity environments, such as future crewed space outposts, but is incremental as it builds on existing robotic and mapping technologies.
The paper tackles the problem of enabling robotic maintenance in space outposts by developing a multi-agent framework for cooperative 3D mapping and change detection, validated using real data from Astrobee robots in ground testing and on the International Space Station.
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.