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Record W2044371533 · doi:10.1117/12.660471

Biologically inspired anthropomorphic arm and dextrous robot hand actuated by smart-material-based artificial muscles

2006· article· en· W2044371533 on OpenAlexafffund
Aaron D. Price, Amor Jnifene, Hani E. Naguib

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2006
Typearticle
Languageen
FieldMaterials Science
TopicShape Memory Alloy Transformations
Canadian institutionsUniversity of TorontoRoyal Military College of CanadaUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSMA*ActuatorShape-memory alloyArtificial muscleRobotic armComputer scienceRobotSmart materialCommercializationBiomimeticsArtificial intelligenceControl engineeringEngineeringMechanical engineeringMaterials science

Abstract

fetched live from OpenAlex

Shape memory alloys (SMA) are a class of smart material having the unique ability to return to a predefined shape when heated. SMA based actuators have the potential to be very compact and low weight. As a result, much research has been devoted to the design of SMA based actuators; however, commercialization has been largely impeded by the small strain capacity inherent to SMA. To address this deficiency, this paper conveys the design of a large-strain SMA actuator (in excess of 30%) whose feasibility is investigated by integrating the actuators as artificial muscles in a two link anthropomorphic arm. The ensuing experimental results indicate that the actuators show great potential for a variety of emerging applications. Finally the design of an SMA based dextrous robotic hand evaluation facility is proposed, and provides a case study illustrating how smart structures provide a superior alternative to conventionally voluminous and heavy prosthetic actuators.

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: Empirical
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 head0.014
GPT teacher head0.224
Teacher spread0.210 · 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

Citations7
Published2006
Admission routes2
Has abstractyes

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Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicShape Memory Alloy TransformationsFrench-language works237,207