Microsatellites-and-Space-Microsystems/pose_estimation_domain_gap
Two methods for solving domain gap in satellite pose estimation in space exploiting vision Transformers.
This project helps operations engineers and mission controllers accurately determine the 3D position and orientation (pose) of a known satellite from a single 2D image captured in space. It takes synthetic training images and real orbital images as input, producing precise satellite pose estimates. This is designed for those managing active chaser spacecraft tasked with servicing uncooperative targets.
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Use this if you need robust and accurate satellite pose estimation for critical space missions, even when your AI models are trained on simulated data.
Not ideal if your mission does not involve autonomous rendezvous and docking or close-proximity operations with other satellites.
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Jupyter Notebook
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Apache-2.0
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Last pushed
Jul 14, 2022
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