Concurrent Redirection and Attitude Control of an Asteroid
Bibliographic record
Abstract
This paper demonstrates the applicability of two low-thrust spacecraft for the task of concurrently redirecting an asteroid and controlling its attitude. Through the use of available observational data, a synthetic near-Earth asteroid, with suitable characteristics for a resource utilization mission, is designed. The asteroid is given an initial orientation and angular velocity, such that it is in a tumbling state. The two spacecraft are attached to the asteroid surface, and employ low-thrust ion thrusters for the attitude control and redirection of the asteroid. The spacecraft first detumble the asteroid body using their torque-inducing thrusters, and then re-orient the asteroid such that the redirection thrusters are aligned with the redirection thrust vector. The spacecraft then ensure the asteroid's orientation is aligned with the redirection thrust vector throughout the entire trajectory transfer maneuver, while ensuring the angular velocity remains bounded around zero. The trajectory design is a low-thrust maneuver, based on Gauss' variational equations, which redirects the asteroid from its orbit about the Sun to rendezvous with Earth. A linear control law is employed for both the detumbling and redirection maneuver with attitude control. The overall performance of the system and the applicability of the approach are discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".