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Record W2968684937 · doi:10.1109/icra.2019.8793962

Kinematic Analysis of a 4-DOF Parallel Mechanism with Large Translational and Orientational Workspace

2019· article· en· W2968684937 on OpenAlexaff
Shoichiro Kamada, Thierry Laliberté, Clément Gosselin

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRobotic Mechanisms and Dynamics
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsWorkspaceParallelogramKinematicsMechanism (biology)Jacobian matrix and determinantScrew theoryDegrees of freedom (physics and chemistry)Computer scienceGravitational singularityParallel manipulatorControl theory (sociology)Topology (electrical circuits)GeometryClassical mechanicsMathematicsMathematical analysisPhysicsArtificial intelligence

Abstract

fetched live from OpenAlex

This paper introduces a novel four-degree-of-freedom (4-DOF) parallel mechanism having 3 translational DOFs and 1 rotational DOF. The mechanism comprises 2 sets of parallelogram linkages, which constrain two of the rotational DOFs of the mechanism. An interesting feature of the mechanism is that it can be driven using 4 parallel sliders mounted on its base. As a result, one of the translational DOFs can be infinitely large. Also, the architecture of the mechanism provides a large rotational DOF in one direction. The kinematic equations of the mechanism are derived and the Jacobian matrices are obtained. The mathematical conditions that lead to singularities are also found. Moreover, a geometric description of the boundaries of the workspace is given, which can be expressed using simple equations. Finally, some design examples are proposed and a prototype is presented.

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: Methods · Consensus signal: none
Teacher disagreement score0.548
Threshold uncertainty score0.788

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 head0.003
GPT teacher head0.183
Teacher spread0.180 · 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
GenreMethods

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
Published2019
Admission routes1
Has abstractyes

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