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Record W2800888367 · doi:10.1139/tcsme-2009-0040

A PLANAR CLOSED-LOOP CABLE-DRIVEN PARALLEL MECHANISM

2009· article· en· W2800888367 on OpenAlexafffundvenue
Hanwei Liu, Clément Gosselin

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2009
Typearticle
Languageen
FieldEngineering
TopicRobotic Mechanisms and Dynamics
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsWrenchJacobian matrix and determinantIntersection (aeronautics)EllipsePlanarTrajectoryMechanism (biology)Parallel manipulatorKinematicsControl theory (sociology)Position (finance)Point (geometry)Inverse kinematicsComputer scienceGravitational singularityLoop (graph theory)Topology (electrical circuits)RobotMathematicsGeometryEngineeringMathematical analysisPhysicsMechanical engineeringClassical mechanicsArtificial intelligenceCombinatoricsComputer graphics (images)

Abstract

fetched live from OpenAlex

A novel architecture of planar closed-loop cable-driven parallel mechanism is introduced in this paper. In this architecture, instead of being wound on spools, the cables form closed loops attached to the end-effector and whose motion is controlled by sliders. By eliminating the spools, it is expected that the new mechanisms will lead to a better accuracy than conventional cable-driven parallel mechanisms. This paper presents the inverse kinematics, the Jacobian matrices and the static equilibrium equations for the new architecture. Using the Jacobian matrices, the singularities of the mechanism are also analyzed. Also, based on the static equation, the available wrench set is determined. It is pointed out that the trajectory of the end-point of a given cable loop is a portion of ellipse. The intersection of the ellipses provides the assembly modes. There can be more than one intersection point of the ellipses at a given position of the sliders. This geometric characteristic is analyzed at the end of the paper.

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 score0.547
Threshold uncertainty score0.868

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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 head0.009
GPT teacher head0.188
Teacher spread0.179 · 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

Citations6
Published2009
Admission routes3
Has abstractyes

Explore more

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