Adaptive ReactionLess motion with joint limit avoidance for robotic capture of unknown target in space
Bibliographic record
Abstract
This paper presents a new trajectory generation algorithm for a space manipulator after capturing an uncooperative tumbling target. In particular, the previously developed Adaptive ReactionLess Control algorithm (ARLC) is extended to obtain minimum base reaction motion of the manipulator with consideration of joint limit constraints. A task-priority redundancy resolution technique is formulated within an adaptive control scheme with the primary task to maintain minimum disturbance to the base and the secondary task to avoid the physical joint limits. This control scheme is intended for use in the transition phase of the capture mission from the instant of capture till the unknown parameters are identified and/or the available post-capture stabilization methods can be applied properly. To verify the validity and feasibility of the proposed concept, MSC.Adams simulation platform is employed to implement a planar base-manipulator-target model as well as the three-dimensional model of Engineering Test Satellite VII system. The numerical results show that the proposed control scheme is able to generate the reactionless maneuver without violating joint limits of the arm, after capture of an unknown tumbling target.
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.
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".