System rigidization and control for post-capture maneuvering of large space debris
Bibliographic record
Abstract
In this paper, we present the results of the investigation on post-capture maneuvering of the Envisat spacecraft that would comprise a sub-task of a larger robotic mission to actively remove this now defunct satellite. The specific task considered is that of rigidizing the chaser-manipulator-Envisat system after the capture of the spacecraft has been executed. The challenge lies in the fact that Envisat is tumbling and thus, its angular momentum must be redistributed during the rigidization maneuver so that at the end, the whole system is rotating as a single rigid body. Two rigidization methods are proposed in the paper: a proportional-integral control of the joint rates to the desired null rates for rigidizing the arm. The second scheme, referred to as redundancy resolution control, generates the desired joint rates which, as a primary objective, satisfy the rigid-body velocity constraint between chaser and target motions and, secondly, dissipates energy of the system to ensure rigidization of the arm. The benefit of this approach is that it can also account for joint limits, which maybe critical to the success of the rigidization maneuver. The two rigidization methods are applied to the chaser-manipulator-Envisat system for three tumbling rates of the Envisat spacecraft. The so-called nominal rate corresponds to the observations collected during the 2013 measurement campaign. The additional two rates considered are 1.5 and 2 times the nominal rate, to allow for the uncertainty in Envisat's spin rate as mission planning must accommodate the worst case scenario. Simulation results are presented which demonstrate that rigidization can be accomplished for the nominal and intermediate spin rates; however, the manipulator arm is not sufficiently strong, for the assumed torque limits, to rigidize the system for the worst case considered.
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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".