On the Design of an Adaptable Underactuated Hand Using Rolling Contact Joints and an Articulated Palm
Bibliographic record
Abstract
Abstract Based on an optimized underactuated finger using rolling contact joints, a novel prosthetic hand is proposed in this paper to increase the adaptability to objects of highly underactuated grippers. The hand has 17 degrees-of-freedom and only one degree of actuation, yielding a robust and simple control. A manually operated thumb, able to reach three stable positions corresponding to the main grasping postures is first presented. Its rolling contact joints, introduce geometric twist and tilt, are designed in an iterative process using 3D modeled contacts. In parallel, the parameters of the thumb are optimized to maximize the distribution of contacts and the ability to hold objects. A joint located inside the hand allows the palm to arch, increasing the opposition of the ring finger, and the little finger to the thumb. The floating mechanism used to distribute the single actuation to the different degrees-of-freedom reduces friction while avoiding the unnecessary blocking of components. Finally, a prototype is designed and built to demonstrate the adaptation capabilities of the hand to diverse objects, which is enhanced by a gravity-dependent closing sequence and the deformation of the palm that maximizes the contribution of each finger. Novel possibilities are also presented such as the grasping and flipping of small objects on a hard surface.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".