Ground-based experiments towards the interception of non-cooperative space debris with a robotic manipulator
Bibliographic record
Abstract
This paper presents an account of the experimentations with a ground-based facility emulating interception scenarios with non-cooperative space debris using a robotic manipulator. A sampling-based motion-planning algorithm is used to autonomously solve the dynamic interception problem without collisions and under velocity, acceleration and jerk constraints. Invariant Kalman filter methodologies are employed to estimate and predict the motion of a neutrally-buoyant airship emulating a free-floating target. Discussions are presented on the mitigation of practical issues of system integration and the operation of a sensitive, but cost-effective, test-bed for aerial neutral-buoyancy experiments. An account of ground-based experiments is presented as well as results showing good success rates on the tested scenarios and methods that constitute the first reported set of experiments on the interception phase of active space debris removal.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".