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Record W2321880439 · doi:10.2514/6.2013-4824

Modeling and Control of Flexible Joint Robotic Manipulator

2013· article· en· W2321880439 on OpenAlexafffundabout
Zheng Zhu, Gangqi Dong

Bibliographic record

VenueAIAA Infotech@Aerospace (I@A) Conference · 2013
Typearticle
Languageen
FieldEngineering
TopicDynamics and Control of Mechanical Systems
Canadian institutionsYork University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComputer scienceManipulator (device)Joint (building)Robot manipulatorControl engineeringControl (management)Mobile manipulatorRobotEngineeringArtificial intelligenceMobile robotStructural engineering

Abstract

fetched live from OpenAlex

Robotic manipulators are often coupled with joint flexibilities which will result in unwanted vibrations during the operation of the manipulators and must be controlled or suppressed. In this paper we first developed the dynamics of a single rigid-link flexible-joint robotic manipulator mathematically. In order to obtain an accurate dynamic model, we take into account of the system factors, such as, joint flexibility, damping and friction. Then an impedance controller was designed to perform accurate positioning as well as residual vibration suppression during the operation based on the precise dynamic model. Numerical simulation and experimentation have also been done to validate the effectiveness of the proposed control scheme. York University, Toronto, Ontario, M3J 1P3, Canada

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: none
Teacher disagreement score0.672
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.017
GPT teacher head0.189
Teacher spread0.172 · 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

Citations2
Published2013
Admission routes3
Has abstractyes

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