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Record W2468050848

Underactuation in robotic grasping hands

2002· article· en· W2468050848 on OpenAlexaff
Lionel Birglen, Clément Gosselin

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRobot Manipulation and Learning
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsUnderactuationReconfigurabilityRobotic handDegrees of freedom (physics and chemistry)Computer scienceControl theory (sociology)EngineeringControl engineeringArtificial intelligenceControl (management)RobotPhysics
DOInot available

Abstract

fetched live from OpenAlex

This paper presents the development of selfadaptive and reconfigurable hands which are versatile and easy to control. These hands have three fingers and each of the fingers has three phalanges. The selfadaptability of the hands is obtained using underactuation. Also, the reconfigurability of the hands is obtained by reorienting the fingers. The design of a three-degree-of-freedom (dof) underactuated finger, used in all the hands, is first intro- duced. A first hand, which has 12 dofs and 6 motors is then presented. Subsequently, by including underactuation among the fingers and coupling their orientation, a second hand with 10 dofs and 2 motors is obtained. Finally, control issues and experimental results are presented.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.038
GPT teacher head0.210
Teacher spread0.172 · 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 designSimulation or modeling
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

Citations265
Published2002
Admission routes1
Has abstractyes

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