Autonomous Computer Vision Embedded Camera

In-space satellite servicing is altering space operations by allowing for in-place upgrades, inspections, deorbiting, and refueling, resulting in considerable cost and time savings for satellite orbital insertion. This capability is crucial for both commercial and government stakeholders, including NASA and the United States Space Force (USSF), who see satellite servicing as critical to national security and space superiority. Companies such as OrbitFab and AstroScale are demonstrating servicing technology for extending satellite life through orbit inspection, refueling, debris removal, and relocation, but they are unable to service legacy satellites that do not have pre-positioned fiducial markers for proximity operations. Satellites with these indicators are regarded as prepared, while those without them are deemed unprepared. Translunar Exports and Servicing Incorporated (Translunar ESI) is developing ACECam (Autonomous Computer Vision Embedded Camera), a Guidance, Navigation, and Control (GNC) sensor system designed for satellite servicing without the need for fiducial markers. This technology will enable autonomous proximity operations for non-prepared satellites and enhance servicing capabilities for prepared satellites, significantly expanding the customer base for satellite servicing. ACECam addresses the growing demand for precise satellite inspection, refueling, and debris removal, especially for the 80-85% of active satellites in Low Earth Orbit (LEO) that currently lack serviceability features. ACECam achieves superior pose estimation and relative state measurements by utilizing state-of-the-art machine learning software trained on data relevant to typical customer satellite operations, significantly improving accuracy over existing systems and other closed-form solutions and enabling unprecedented pose estimating without the need for pre-positioned fiducial markers. For a number of reasons, this technique promises a revolutionary new class of satellite servicing capabilities. The AI algorithms of ACECam, which make use of sophisticated computer vision models for precise target recognition and tracking of both prepared and non-prepared satellites, are its key attributes, which are supported by real-time processing, made possible by on-board processing capabilities to enable in-the-moment data analysis and decision-making. Small satellites and cubesats can utilize ACECam because of its compact design, which fits into a 1U volume. With its cutting-edge technological features and small design, ACECam provides a game-changing solution.