Holding Performance of an Adaptive Magnetorheological Fluid-Based Robotic Claw
Bibliographic record
Abstract
This study addresses the holding performance of an adaptive magnetorheological fluid (MRF)-based robotic claw that can grasp a wide range of objects satisfying various grasping task requirements. To this end, a two-finger type of MRF-based robotic claw was proposed in this study. Two magnetorheological (MR) grippers with MR elastomer (MRE) bladders were mounted at the end of each finger. A target object was placed between these two MR grippers and was grasped by manually adjusting the distance between these two fingers. This adjustment of the distance between the two fingers results in a change in the normal force applied to the object. The holding forces of the MRF-based robotic claw with respect to both applied normal forces and magnetic field strengths were experimentally measured using an Instron material testing machine. From the measured holding forces, the dynamic and static holding forces, controllable holding forces, and holding coefficients were determined for the evaluation of the holding performances of the MRF-based robotic claw. The feasibility of the MRF-based robotic claw was experimentally confirmed.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".