Computer-Vision-Driven Artificial Potential Function Guidance and Adaptive Control for Spacecraft Proximity Operations
Why this work is in the frame
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Bibliographic record
Abstract
This research addresses the growing issue of space debris by developing advanced computer vision, guidance, and control techniques for autonomous docking in proximity operations. Specifically, this work develops these technologies to present an experiment where a chaser platform autonomously docks with a cooperative spinning target while avoiding an uncooperative obstacle. A stereovision system using ArUco markers tracks the target’s pose in real-time, while an unscented Kalman filter processes the data. The obstacle is detected through bounding box manipulation and stereo disparity principles. A novel artificial potential function guidance law, herein adapted for spinning targets, calculates a collision-free trajectory, which is tracked using a real-time adaptive control law. Experimental validation at Carleton University’s Spacecraft Proximity Operations Testbed confirms the effectiveness of the proposed system.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it