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Record W2108624774 · doi:10.1109/isie.2008.4677129

Hardware-in-the-loop simulation of an impedance controlled robot using a direct-drive test bench

2008· article· en· W2108624774 on OpenAlexaff
Philippe Hamelin, Pascal Bigras, Julien Beaudry, Sylvain Lemieux, Michel Blain

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicReal-time simulation and control systems
Canadian institutionsPolytechnique MontréalÉcole de Technologie SupérieureHydro-Québec
Fundersnot available
KeywordsHardware-in-the-loop simulationTest benchRobotController (irrigation)SimulationImpedance controlComputer scienceLoop (graph theory)Control engineeringControl theory (sociology)Computer hardwareEngineeringControl (management)Embedded systemArtificial intelligence

Abstract

fetched live from OpenAlex

This article presents the hardware-in-the-loop simulation of an impedance control applied to a virtual robot acting on a stiff environment. A test bench, which is composed of a direct-drive manipulator and a stiff environment, is used as the hardware part. A hardware-in-the-loop controller is used to command the manipulator so that it reproduces the virtual robot dynamics. Hence, the latter virtually acts on the real environment. Experimental results of the hardware-in-the-loop simulation are compared to pure simulation. It shows that both results are very similar and therefore the real robot can accurately reproduce the virtual robot dynamics.

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 score0.055
Threshold uncertainty score0.474

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 head0.023
GPT teacher head0.261
Teacher spread0.238 · 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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