Spacecraft Pose Estimation
Overview
The field estimates a spacecraft’s six-degree-of-freedom pose relative to a camera or another vehicle, often when the target is uncooperative and its geometry is unknown. Methods use monocular or stereo images, depth and LiDAR, or event cameras, with approaches including keypoint and heatmap networks, geometric feature matching with Perspective-n-Point solvers, and temporal tracking or Kalman filtering. Researchers train and evaluate systems on benchmarks such as SPEED+, SPADES, and SwissCube, using synthetic data, sim-to-real adaptation, and increasingly diverse multimodal datasets. Accuracy is improving, but generalization to unseen spacecraft, difficult lighting, small components, symmetry, and tracking drift remains challenging, alongside the need for efficient onboard inference.
Latest papers
19 papers3 papers in the last four weeks, level with the four weeks before. 0.0% of all new papers.