Design of a 6 degree of freedom anthropomorphic robotic jaw
Bibliographic record
Abstract
We have created a 6 DOF robotic jaw capable of producing, in real-time, the complex set of motions described by the human jaw during speech or mastication. The jaw is designed to fit within a larger robotic human figure such as the head, neck and torso of the 25 DOF Infanoid. [Kozima, Hideki: Infanoid: A Babybot that Explores the Social Environment, K. Dautenhahn et al. (eds.), Socially Intelligent Agents: Creating Relationships with Computers and Robots, Kluwer Academic Publishers, pp. 157–164, 2002]. The produced mechanical prototype has been designed to accommodate a prosthesis mandible with dentures. The mechanism could fit within the skull of the average man; where it would occupy less than 1/3 of the skull cavity. Two TMJs (temporomandibular joints) support the prosthesis, where each is driven by a 3 DOF parallel manipulator. In order to combine the motion of both manipulators each TMJ is capable of 3 DOF. The system is controlled via a USB port using software that models the human skull including collision detection mechanisms. The jaw allows for linear control, zero-backlash, and up to three times exaggerated mobility ranges making it also suitable for speech research, facial gesture affect research and dentistry applications.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".