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Record W2060429363 · doi:10.1002/rob.20013

The Synthesis of Three‐Degree‐of‐Freedom Planar Parallel Mechanisms with Revolute Joints (3‐RRR) for an Optimal Singularity‐Free Workspace

2004· article· en· W2060429363 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Robotic Systems · 2004
Typearticle
Languageen
FieldEngineering
TopicRobotic Mechanisms and Dynamics
Canadian institutionsUniversité de Moncton
Fundersnot available
KeywordsWorkspaceJacobian matrix and determinantMechanism (biology)SingularityGravitational singularityPlanarRevolute jointComputer scienceComputationControl theory (sociology)Parallel manipulatorTopology (electrical circuits)MathematicsAlgorithmGeometryMathematical analysisRobotArtificial intelligenceApplied mathematicsPhysicsControl (management)

Abstract

fetched live from OpenAlex

Abstract In this paper, a method is presented for the synthesis of 3‐ R RR planar parallel mechanisms. The method uses a genetic algorithm while considering three different design criteria: the optimization of the mechanism workspace to approach a prescribed workspace, the maximization of the mechanism's dexterity, and the avoidance of singularities inside the mechanism workspace. It is shown that, for a given mechanism, some working modes do not have any corresponding singularity curves located inside the mechanism workspace. Furthermore, a case is presented where, for a given orientation range of the mechanism's end‐effector, there are no parallel singularities located inside the workspace. Finally, two methods are described and compared to deal with the nonuniform units of the mechanism's Jacobian matrix during the dexterity computation. © 2004 Wiley Periodicals, Inc.

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.

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)0.001
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: Methods
Teacher disagreement score0.058
Threshold uncertainty score0.770

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.022
GPT teacher head0.213
Teacher spread0.191 · 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