Spacecraft Pose Tracking via Kinematic Prediction and Selective Event Correction
Spacecraft Pose Tracking via Kinematic Prediction and Selective Event Correction
This research proposes OA-EI, a method for spacecraft pose tracking that combines kinematic prediction with selective event correction. The approach uses a constant-body-twist model and an event encoder to refine predictions, achieving significant reductions in rotation and translation errors. Evaluation on physical-event trajectories shows improvements in accuracy and reliability, with error reductions of 62.2% and 60.9% respectively. The method is tested on Jetson Orin Nano, with measured update times of 44.56 milliseconds at the median.
Source: arXiv Robotics — research abstracts · Read original article ↗
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Publisher-reported claims, with original evidence. These results have not been independently verified by RoboSignal.
Reported numbers
rotation error
41.63
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taining propagated axial depth. Candidate magnitudes come from a bounded Scale Gate and a deterministic activity factor, with empty windows returning the prediction unchanged. Evaluation uses four FRESH physical-event trajectories, twenty rollout starts, and three training seeds. Each rollout starts from two reference poses and then uses self-estimates. At 7.7 seconds, rotation and translation errors fall from 41.63{
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taining propagated axial depth. Candidate magnitudes come from a bounded Scale Gate and a deterministic activity factor, with empty windows returning the prediction unchanged. Evaluation uses four FRESH physical-event trajectories, twenty rollout starts, and three training seeds. Each rollout starts from two reference poses and then uses self-estimates. At 7.7 seconds, rotation and translation errors fall from 41.63{
Open source S3
Source：arXiv Robotics — research abstracts · arxiv.org