Research on Bending and Torsion Properties of Bionic Square Continuum Robot
Bibliographic record
Abstract
Continuum robot, often taking inspiration from biomimetics, is an exciting novel research field and has great capability. The higher stiffness continuum robot may be inspired by the biology, such as seahorse, pipefish and pipehorse, which has both strong skeleton and great dexterity. In this paper, we present a novel square continuum robot (SCR), according to the simplified model of those square shape fish, in which both the bending curvature and torsional angle are controllable. The idea is to employ square components to mimic the armor and connected those components with ball pair and soft skin. The bending and twisting capabilities of SCR are explored in both numerical model and prototype, while a comparison has been done to analysis the dexterity difference in different situations. Based on the numerical model, relationship between angle-moment in pure bending and angle-torque in pure torsion are shown respectively in simulation curve. This topic is expected to provide a type of new structure for continuum robot, which not only expands the dexterity, but also make the robot stiffer, and provide basic for the further study.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".