Model predictive control for an AUV with dynamic path planning
Why this work is in the frame
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Bibliographic record
Abstract
This paper investigates the model predictive control (MPC) for an autonomous underwater vehicle (AUV). We aim to develop a tracking control algorithm integrated with a dynamic path planning for the AUV. Considering that the effective range of onboard sensors cannot be large, we formulate the path planning problem into a receding horizon optimization framework with spline path templates. Once the local optimal path is constructed for the current time, it is viewed as a reference trajectory of the vehicle. In order to control the depth of AUV simultaneously and to have a friendly interaction with the dynamic path planning method, a nonlinear model predictive control (MPC) scheme is adopted. The simulation results demonstrate the effectiveness of the proposed tracking control algorithm.
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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 it