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Record W2114776014 · doi:10.1109/iros.2008.4651039

Admittance control of a human centered 3 DOF robotic arm using Differential Elastic Actuators

2008· article· en· W2114776014 on OpenAlexaff
Marc-Antoine Legault, M.-A. Lavoie, François Cabana, P. Jacob-Goudreau, Dominic Létourneau, François Michaud, Michel Lauria

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicProsthetics and Rehabilitation Robotics
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsActuatorTorsion springMechanical impedanceTorqueControl theory (sociology)StiffnessSpring (device)Harmonic driveElectrical impedanceRobotic armMechanical systemDC motorAdmittanceComputer scienceEngineeringPhysicsElectrical engineeringMechanical engineeringStructural engineeringArtificial intelligence

Abstract

fetched live from OpenAlex

This video shows the functionalities of a 3 serial DOF robotic arm. Each DOF is actuated with a patent pending differential elastic actuator (DEA) [1,2]. Compared to the abundantly studied series elastic actuator [3,4], DEA uses a differential coupling between a high impedance mechanical speed source and a low impedance mechanical spring. Possible implementations of a mechanical differential include the use of a standard gearbox, harmonic drive, cycloidal gearbox, bar mechanism, cable mechanism and all other mechanism that implement a differential function between three mechanical ports. For the implementation reported in this video, we used a harmonic drive for a very compact design. A passive torsion spring (thus the name elastic), with a known impedance characteristic corresponding to the spring stiffness, is used, with an electrical DC brushless motor. A non-turning sensor connected in series with the spring measures the torque output of the actuator.

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 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: Empirical
Teacher disagreement score0.370
Threshold uncertainty score0.445

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)0.0000.000

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 head0.019
GPT teacher head0.230
Teacher spread0.212 · 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 teacher head, 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

Citations5
Published2008
Admission routes1
Has abstractyes

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