Development of a Hardware Demonstration Platform for Multi-Spacecraft Reconnaissance of Small Bodies

The next frontier in space exploration involves visiting some of the 2 million small bodies scattered throughout the solar system. However, these missions are expected to be challenging due to the surface irregularities of these bodies and the very low gravity, which makes steps like getting into orbit very complex. For these reasons, reconnaissance is crucial for small body exploration before taking on ambitious orbital, surface, and sample-return missions. Our previous work developed IDEAS, an automated design software for small body reconnaissance mission development using spacecraft swarms. A critical challenge to furthering such designs is the lack of hardware demonstration platforms for interplanetary spacecraft operations. In this paper, we present MAPS (Multi-Agent Photogrammetry of Small bodies), a hardware platform to demonstrate critical reconnaissance operations of multi-spacecraft missions identified by the IDEAS framework. MAPS uses UAVs as the autonomous agents that perform reconnaissance operations. The UAVs use their visual feed to generate a 3D surface map of a small body mockup, which is encountered along their flight path. In this paper, we examine the various design elements of a small body surface reconstruction mission inside the MAPS testbed. These elements are used for designing reference trajectories of the participating UAVs, which is enforced using a tracking feedback control law. We then formulate the small-body mapping problem as an MINLP problem, which is handled by the Automated Swarm Designer module of the IDEAS framework. The solutions are implemented inside the MAPS, and shape models generated from the UAV feeds are compared.