Bibliographic record
Abstract
Abstract This article presents a novel telepresence system equipped on the remotely operated vehicle to enhance underwater manipulation capabilities. We achieve this by combining a waterproof camera with a multi-degrees-of-freedom underwater manipulator, which provides competitive mobility and flexibility compared to the conventional visual feedback method based on an on-vehicle camera. The suggested method solves the problem of view selection and adjustment; however, it cannot eliminate the visual jitter as it is impossible to keep a floating vehicle position and the pose change of the vehicle immediately delivered to the camera arm. Therefore, we propose a kinematic control law based on the null-space-based framework to coordinate the arm-based camera motion with the manipulation task performed with the operating arm. This underwater vision enhancement technology only needs the desired pose of the end camera to automatically calculate the suitable configuration of the camera arm, which reduces the burden on the operator and allows the operator to concentrate on the operation task. We also extended the method to meet three common underwater operation scenarios. Simulation results demonstrate that the proposed telepresence system performs remarkably well in reducing view jitter and maintaining field-of-view (FOV) stability, establishing it as a viable option for inspection and maintenance applications.
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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".