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Autonomous Multi-Spectral Relative Navigation, Active Localization, and Motion Planning in the Vicinity of an Asteroid

Panagiotis Tsiotras
Georgia Institute of Technology

ESI 2017 Quad Chart Panagiotis Tsiotras

Several probing missions of various types to near Earth small bodies and asteroids have been conducted and proven to have great scientific return. These include flybies, such as Mariner 9, simple rendezvous such as NEAR-Shoemaker and Dawn, sample return such as Hayabusa, and lander/impactor such as Rosetta. Such missions have set space exploration milestones, captured the public’s attention, and paved the way for ambitious future projects in the likes of asteroid capture and even mining for resources.  Remote, human-supervised navigation and guidance for these future missions is a real challenge owing to the large distances from the Earth, Evolved spacecraft probes with increased autonomous on-board relative navigation and guidance capabilities can reduce the time and manpower required for the characterization and the subsequent navigation phases in deep space missions, thus reducing mission cost and complexity. We propose to develop, test and implement the necessary theories and algorithms for inspection, geometric reconstruction and tracking of a small celestial body (e.g., asteroid) in space, using different sensor modalities, including both passive sensors (visual light and infrared cameras) and time-of-flight (TOF) 3D active sensors such as flash-LiDARs. Traditional localization and shape reconstruction methods developed primarily for ground robots need to be modified in order to address the environmental challenges encountered in space (e.g., illumination conditions, absence of background inertial feature points), as well as spacecraft onboard restrictions (limited power, fuel, and computational resources). The proposed algorithms will advance the state-of-the-art in autonomous small body navigation and maneuvering for a broad class of future small celestial body missions, including remote characterization, sample return, resource utilization, etc.

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