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Record W3082516437 · doi:10.1115/1.4048258

Rotational Low-Impedance Physical Human–Robot Interaction Using Underactuated Redundancy

2020· article· en· W3082516437 on OpenAlexafffund
Julien M. Audet, Clément Gosselin

Bibliographic record

VenueJournal of Mechanisms and Robotics · 2020
Typearticle
Languageen
FieldEngineering
TopicRobot Manipulation and Learning
Canadian institutionsUniversité Laval
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of Canada
KeywordsUnderactuationRedundancy (engineering)RobotCounterweightControl theory (sociology)Context (archaeology)Impedance controlElectrical impedanceComputer scienceControl engineeringEngineeringSimulationMechanical engineeringArtificial intelligenceElectrical engineering

Abstract

fetched live from OpenAlex

Abstract This paper extends the concept of underactuated redundancy for physical human–robot interaction (pHRI) in a context of industrial assembly by introducing a novel 1-dof gravity balanced rotational manipulator. The proposed architecture consists of a rotational active counterweight with a passive joint equipped with an encoder. The proposed architecture is first described, and the static equilibrium conditions are used to describe the operation of the mechanism. Then, alternative architectures are briefly introduced. Finally, an experimental validation is provided to demonstrate the viability of the concept for rotational low impedance pHRI.

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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.046
GPT teacher head0.283
Teacher spread0.237 · 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

Citations13
Published2020
Admission routes2
Has abstractyes

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