Design of a novel biologically inspired robot fish with low cost
Bibliographic record
Abstract
Being a novel form of underwater vehicle, the robot fish has the advantages of good maneuverability, quick response, high propulsion efficiency, and low noise. It is widely used in marine biological observation, marine water quality monitoring, submarine pipeline inspection, and exploration. It is one of the hot research topics in the marine field. Compared to the robot fish propulsion mechanism using rigid components, which has problems of no adaptability to underwater motion, and low motion efficiency and inability to imitate the fish body to perform flexible swings, the soft robot fish has higher swimming efficiency, and is the focus of this project. In this work, the design of a novel soft robot fish, with focus on actuation system design, is proposed. The actuation system is based on the motor-driven bevel gear mechanism, which has the advantages of realizing rapid speed regulation, two-way drive, and adjustment range in a small space. One advantage of our design is its straightforward assembly and relatively simple fabrication, which can be completed mainly using 3D printing technology. Three different designs are proposed, based on a comprehensive comparison in terms of efficiency, reliability, and fabrication cost, one design is chosen to be fabricated and tested. The test focuses on the relationship between the swing amplitude, frequency, and swimming speed of the tail. The experiment is mainly divided into two parts: the test of driving the tail of the propulsion mechanism; and the robot fish underwater movement. The test results show that the design achieves the expected motion goal and is engineering feasible, which provides a new solution for the design of the robot fish.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".