Parametric mechanical design and optimisation of the Canterbury Hand.
Bibliographic record
Abstract
As part of worldwide research humanoid robots have been developed for household, industrial and exploratory applications. If such robots are to interact with people and human created environments they will require human-like hands. The objective of this thesis was the parametric design and optimisation of a dexterous, and anthropomorphic robotic end effector. Known as the ‘Canterbury Hand’ it has 11 degree of freedoms with four fingers and a thumb. The hand has applications for dexterous teleoperation and object manipulation in industrial, hazardous or uncertain environments such as orbital robotics. The human hand was analysed so that the Canterbury Hand could copy its motions, appearance and grasp types. An analysis of the current literature on experimental prosthetic and robotic hands was also carried out. A disadvantage of many of these hand designs was that they were remotely powered using large, heavy actuator packs. The advantage of the Canterbury Hand is that it has been designed to hold the motors, wires, and circuit boards entirely within itself; although a belt carried battery pack is required. The hand was modelled using a parametric 3D computer aided design (CAD) program. Two different configurations of the hand were created in the model. One configuration, as a dexterous robot hand, used Ø13mm 3 Watt DC motors, while the other used Ø10mm, 0.5 Watt DC motors (although this hand is still slightly too large for a general prosthesis). The parts within the hand were modelled to permit changes to the geometry. This was necessary for the optimisation process. The bearing geometry of the finger and thumb linkages, as well as the thumb rotation axis was optimised for anthropomorphic motion, appearance and increased force output. A design table within a spreadsheet was created to interact with the CAD models of the hand to quickly implement the optimised geometry. The work reported in this thesis has shown the possibilities for parametric design and optimisation of an anthropomorphic, dexterous robotic hand.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".