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Record W2107869943 · doi:10.1109/iros.1998.727433

Workspace analysis of a 3-DOF parallel mechanism

2002· article· en· W2107869943 on OpenAlexaff
Juan A. Carretero, Meyer Nahon, Ron P. Podhorodeski

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRobotic Mechanisms and Dynamics
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsWorkspaceJacobian matrix and determinantMechanism (biology)Computer scienceSubspace topologySet (abstract data type)KinematicsControl theory (sociology)RobotMathematicsArtificial intelligenceApplied mathematicsPhysicsControl (management)

Abstract

fetched live from OpenAlex

A variety of definitions of the workspace of a mechanism can be found in the literature. In this paper, the dexterous workspace is defined as a subspace of the reachable workspace having an adequate performance of a dexterity measure, e.g. the condition number of the Jacobian matrix. The dexterous workspace of a 3-DOF parallel mechanism is analyzed. In order to study the changes of the workspace volume as the architectural parameters are changed, several plots of the dexterous workspace are presented. The shape, size and symmetry of the workspace is found to be very dependent on the particular set of architectural parameters chosen for the mechanism.

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 categoriesInsufficient payload (model declined to judge)
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 score0.442
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.182
Teacher spread0.170 · 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.

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

Citations28
Published2002
Admission routes1
Has abstractyes

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