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Record W2126924659 · doi:10.1243/09596518jsce605

Compact dynamic models for the tripteron and quadrupteron parallel manipulators

2009· article· en· W2126924659 on OpenAlexafffund
Clément Gosselin

Bibliographic record

VenueProceedings of the Institution of Mechanical Engineers Part I Journal of Systems and Control Engineering · 2009
Typearticle
Languageen
FieldEngineering
TopicRobotic Mechanisms and Dynamics
Canadian institutionsUniversité Laval
FundersCanada Research Chairs
KeywordsParallel manipulatorKinematicsComputer scienceSimple (philosophy)Dynamic equationRobotControl theory (sociology)Network topologyMotion (physics)Degrees of freedom (physics and chemistry)Topology (electrical circuits)Artificial intelligenceMathematicsControl (management)Nonlinear systemPhysics

Abstract

fetched live from OpenAlex

This paper proposes compact dynamic models for the tripteron, a three-degree-of-freedom (DOF) translational parallel manipulator and the quadrupteron, a four-DOF Schönflies-motion parallel manipulator. First, the architecture and kinematics of the tripteron and quadrupteron are briefly recalled. Then, the dynamic models are derived based on the Newton-Euler approach and a judicious sequencing of the application of the equations. It is shown that the dynamic models obtained are computationally efficient and conceptually simple. Therefore, the models can be used to improve the control of robots, especially in applications where high accelerations are required. The general approach proposed for the derivation of the models can be extended to other topologies and geometries of parallel manipulators.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.011
GPT teacher head0.197
Teacher spread0.187 · 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 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

Citations28
Published2009
Admission routes2
Has abstractyes

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Same venueProceedings of the Institution of Mechanical Engineers Part I Journal of Systems and Control EngineeringSame topicRobotic Mechanisms and DynamicsFrench-language works237,207