A novel bionic gripper based on the front tarsi of scutigers
Bibliographic record
Abstract
A novel bionic gripper with bristles is designed based on the biological structure of the front tarsi of scutigers, and its simulation model is established. It was verified that the proposed bionic gripper not only achieved the expected gripping action but also completed the pinching motion with better grasping performance. Related parameters, such as displacement, velocity, acceleration, force, and torque, were also analyzed. Friction contact finite element analysis of the bionic gripper with bristle structure was performed using ABAQUS and compared with the control group. The finite element analysis results showed that the bristles could effectively improve the capture efficiency of the bionic gripper. The diameter and density of the bristles in the bionic gripper were optimized, and their influence on the gripping efficiency was analyzed. This study provides a reference for the structural design of bionic grippers and the practical application of bionic non-smooth surfaces.
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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".