A controller topology for maneuvering a floating object via direct pushing with a ship
Bibliographic record
Abstract
This paper presents a controller topology for maneuvering a floating object via direct pushing with a ship. The approach focuses on two primary tasks: the approach phase, where the ship aligns with and closes the distance to the object, and the manipulation phase, where the object is controlled while maintaining physical contact. The proposed control system combines trajectory planning with maneuvering the object by pushing at a strategically chosen point of contact, maintaining stability as it is guided toward the goal position. The controller is designed to handle the complex dynamics of ship-ice interactions and to mitigate external disturbances, including wind, waves, and currents. The control system is implemented and evaluated through both simulation and experimental studies. Simulations are used to assess the robustness of the controller topology and its ability to perform effectively across a range of geometric configurations. Experimental results investigate the behavior of the control framework in model test scenarios, offering insights into practical considerations such as contact force variability and complex hydrodynamics not modeled in simulation. Although this work focuses on single-agent manipulation of a floating object, it paves the way for future extensions to more complex scenarios. Future research will explore the use of multiple ships working cooperatively as a swarm to manipulate multiple floating objects, with an emphasis on minimizing interaction effects and ensuring effective coordination. These advancements aim to address broader challenges in Arctic ice management and other maritime applications involving collaborative systems for floating object control.
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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".