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Completed TRL 1 (started at 1, targeting 3)
Simultaneous Localization and Mapping (SLAM) attempts to estimate a vehicle’s position and orientation (localization) and the location of an initially unknown number of features in the environment (mapping) simultaneously. The satellite relative navigation and pose estimation problem can be considered a 3D SLAM problem where we are estimating the position, velocity, attitude, and attitude rate of the primary satellite relative to the target satellite while simultaneously estimating a map of the target features. The goal of this project is to demonstrate the feasibility and effectiveness of using SLAM for autonomous, precise relative navigation and pose estimation without reliance on GNSS for RPO applications such as satellite proximity operations for inspection, satellite rendezvous for servicing, and near asteroid/comet navigation.
Autonomous relative navigation and pose estimation enables a number of missions of interest to NASA including satellite inspection and servicing, rendezvous and docking, and small body (asteroid and comet) exploration. Due to its enhanced ability to estimate in the presence of noisy measurements and clutter, SLAM has the potential to significantly improve our ability to perform relative navigation and pose estimation with an asteroid or satellite that is not well known beforehand, operate in a wider range of lighting conditions or in a lower signal-to-noise environment.
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