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Record W1992260861 · doi:10.5194/ms-1-27-2010

Active gesture-changeable underactuated finger for humanoid robot hand based on multiple tendons

2010· article· en· W1992260861 on OpenAlexaboutno aff
Demeng Che, Wenbin Zhang

Bibliographic record

VenueMechanical sciences · 2010
Typearticle
Languageen
FieldEngineering
TopicRobot Manipulation and Learning
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsUnderactuationGestureFunction (biology)EngineeringMotion (physics)Computer scienceArtificial intelligenceSimulationControl (management)Control engineering

Abstract

fetched live from OpenAlex

Abstract. The concept called gesture-changeable under-actuated (GCUA) function is utilized to improve the dexterities of traditional under-actuated hands and reduce the control difficulties of dexterous hands. Based on GCUA function, a novel mechanical finger by multiple tendons: GCUA-T finger, is designed. The finger uses tendon mechanisms to achieve GCUA function which includes traditional underactuated (UA) grasping motion and special pre-bending (PB, or pre-shaping) motion before UA grasping. Operation principles and force analyses of the fingers are given, and the effect of GCUA function on the movements of a hand is discussed. The finger can satisfy the requirements of grasping and operating with low dependence on control system and low cost on manufacturing expenses, which develops a new way between dexterous hand and traditional under-actuated hand. This paper was presented at the IFToMM/ASME International Workshop on Underactuated Grasping (UG2010), 19 August 2010, Montréal, Canada.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.045
GPT teacher head0.273
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2010
Admission routes1
Has abstractyes

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