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Record W2019913969 · doi:10.1109/iros.2014.6942601

A dual-motor robot joint mechanism with epicyclic gear train

2014· article· en· W2019913969 on OpenAlex
Vincent Babin, Clément Gosselin, Jean-François Allan

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRobot Manipulation and Learning
Canadian institutionsHydro-QuébecUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMechanism (biology)Dual (grammatical number)RobotJoint (building)Computer scienceGear trainRobot kinematicsControl engineeringMobile robotAutomotive engineeringEngineeringArtificial intelligencePhysicsBacklashStructural engineering

Abstract

fetched live from OpenAlex

This paper presents the concept of a new robotic joint composed of two electric motors as inputs, an epicyclic gearing system for the transmission, and a single output. The proposed joint mechanism has a wider range of speed and torque performances comparatively to a traditional robot joint using a single motor and gearbox. The dynamic equations for the mechanical transmission system are given and a dual-motor joint mechanism is designed and prototyped to test this new concept of robotic joint. Also, the potential advantages of this joint concept for the design of manipulators for which a wide range of performances are desired are discussed. This work is motivated by the development of field robots designed for the operation and maintenance tasks in power distribution lines.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.940
Threshold uncertainty score0.724

Codex and Gemma teacher scores by category

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 head0.017
GPT teacher head0.193
Teacher spread0.176 · 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

Quick stats

Citations10
Published2014
Admission routes2
Has abstractyes

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