Efficient Control of an AUV-Manipulator System: An Application for the Exploration of Europa
Bibliographic record
Abstract
Autonomous control of a robotic manipulator mounted on a submersible autonomous underwater vehicle (AUV) is simulated with various strategies employing combinations of feedback and feedforward control. Feedforward compensation of the manipulator motion is accomplished using a model of the system kinematics and dynamics. Hydrodynamic effects including drag, buoyancy, and added mass, as well as the reaction of the vehicle, are all compensated. Effective manipulator position control is accomplished through stabilization of the vehicle orientation and system barycenter. Stabilization of the vehicle position using feedback and/or feedforward control is also considered for comparison. Compensation of the hydrodynamic effects while stabilizing the vehicle orientation and allowing vehicle translation resulted in a significant reduction in power consumption. Although experimental verification of the results is required, the improvement in efficiency may be beneficial for submersible vehicles operating in extremely remote conditions or extraterrestrial environments such as the oceans of Jupiter's moon, Europa.
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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".