Naturally Compliant Dexterous Anthropomorphic Hand via Novel Modular Soft-Rigid Hybrid Robotics Approach: Design Rationale, Assembly Methods, and Evaluation
Bibliographic record
Abstract
In this paper, we propose a modular soft-rigid hybrid (MSRH) approach for designing a highly anthropomorphous and dexterous robotic hand. This MSRH approach allows the robotic hand to possess an inherently soft and compliant interface suitable for pHRI while maintaining the structural rigidity of the robot with the usage of rigid skeletons. We share the details of the design rationale, fabrication and assembly methods, and evaluation of the first prototype. Even though the presented prototype is scaled to be 125% of the average human hand, the mechanical components only weigh less than 450 g. The modular design approach allows the MSRH hand to have low manufacturing costs and a short lead time. Creation of the presented prototype costs less than ${\$}$100 CAD and can be built in three days from scratch with two-person labour. The usage of pneumatic soft robotic actuators also provides flexibility over choosing the number of controlled DOF and joint coupling. This hence provides a new angle to tackle spatial constraint that normally arises in robotic hand design with increased anthropomorphism. Lastly, the dexterity of the proposed hand is demonstrated by evaluating the hand using taxonomies highly relevant to replicating tasks humans perform daily.
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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 | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".