A trajectory tracking controller for an underwater hexapod vehicle
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper describes work done in the modeling and control of a low speed underwater vehicle that uses paddles instead of thrusters to move in the water. A review of previously modeled vehicles and of controller designs for underwater applications is presented. Then, a method to accurately predict the thrust produced by an oscillating flexible paddle is developed and validated. This is followed by the development of a method to determine the ideal paddle motion to produce a desired thrust. Several controllers are then developed and tested using a numerical simulation of the vehicle. We found that some model-based controllers could improve the performance of the system while others showed no benefit. Finally, we report results from experimental trials performed in an open water environment comparing the performance of the controllers. The experimental results showed that all the model-based controllers outperform the simple proportional-derivative controller. The controller giving the best performance was the model-based nonlinear controller. We also found that the vehicle was able to follow a change of a roll angle of 90 degrees in 0.7 s and to precisely follow a sinusoidal trajectory with a period of 6.28 s and an amplitude of 5 degrees.
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.
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