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Record W2990689231 · doi:10.1115/detc2019-97083

Deflection Maps of Elastic Catenary Cable-Driven Robots

2019· article· en· W2990689231 on OpenAlexaff
Leila Notash

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Surface Polishing Techniques
Canadian institutionsQueen's University
Fundersnot available
KeywordsCatenaryWorkspaceWrenchDeflection (physics)RobotStructural engineeringComputer scienceEngineeringMechanical engineeringPhysicsOpticsArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract In this paper, the cable tension and platform deflection of cable-robots are investigated. The significance of cable density, elasticity and cross-sectional area; platform mass, radius and center of mass; external wrench and platform orientation on the cable tension, platform deflection and workspace of the planar cable robots is investigated. It is shown that, in addition to cable mass, the effect of external wrench on the workspace of catenary cable model could be more prominent. Moreover, design issues and parameters affecting the manipulator deflection are examined, and those that would result in disjointed workspace regions and deflection maps are identified. It is presented that the change in deflection is gradual throughout the workspace for constant external wrench. For the catenary model, depending on the cable properties, platform orientation, manipulator design, and external wrench, the workspace with deflection limit may consist of disconnected regions.

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 score0.574
Threshold uncertainty score0.333

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)0.0000.000

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 head0.008
GPT teacher head0.218
Teacher spread0.210 · 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
Published2019
Admission routes1
Has abstractyes

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