Type Synthesis ofLinkage-Driven Self-Adaptive Fingers
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract This paper aims at providing a method to synthesize mechanical architectures of self-adaptive robotic fingers driven by linkages. Self-adaptive mechanisms are used in robotic fingers to provide the latter with the ability to adjust themselves to the shape of the object seized without any dedicated electronics, sensor, or control. This type of mechanisms has been known for centuries but the increased capabilities of digital systems have kept them in the shadows. Recently, because of the lack of commercial and industrial success of complex robotic hands, self-adaptive mechanisms have attracted much more interest from the research community and several prototypes have been built. Nevertheless, only a handful of prototypes are currently known. It is the aim of this paper to present a methodology that is able to generate thousands of self-adaptive robotic fingers driven by linkages with two and three phalanges. First, potential kinematic architectures are synthesized using a well-known technique. Second, the issue of proper actuation and passive element(s) selection and location is addressed.
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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 it