Automated satellite proximity operations is an increasingly relevant area of mission operations for the US Air Force with potential to significantly enhance space situational awareness (SSA). Simultaneous localization and mapping (SLAM) is a computer vision method of constructing and updating a 3D map while keeping track of the location and orientation of the imaging agent inside the map. The main objective of this research effort is to design a monocular SLAM method customized for the space environment. The method developed in this research will be implemented in an indoor proximity operations simulation laboratory. A run-time analysis is performed, showing near real-time operation. The method is verified by comparing SLAM results to truth vertical rotation data from a CubeSat air bearing testbed. This work enables control and testing of simulated proximity operations hardware in a laboratory environment. Additionally, this research lays the foundation for autonomous satellite proximity operations with unknown targets and minimal additional size, weight, and power requirements, creating opportunities for numerous mission concepts not previously available.
Monocular SLAM Method to Estimate Relative Pose During Satellite Proximity Operations
2015
118 pages
Report
No indication
English
Relative Pose and Inertia Determination of Unknown Satellite Using Monocular Vision
DOAJ | 2018
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