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Record W2164277546 · doi:10.24908/pceea.v0i0.3774

RVS4W: A VISUALIZATION TOOL FOR ROBOT DESIGN

2011· article· en· W2164277546 on OpenAlexafffundvenueabout
Waseem A. Khan, Jorge Angeles

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2011
Typearticle
Languageen
FieldEngineering
TopicRobot Manipulation and Learning
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsVisualizationUploadRobotWindow (computing)Computer scienceHuman–computer interactionRoboticsGraphicsArtificial intelligenceComputer graphics (images)World Wide Web

Abstract

fetched live from OpenAlex

The Robot Visualization System for Windows (RVS4W) is a cross-platform version of its predecessor, the Robot Visualization System (RVS). Both RVS and RVS4W were developed at McGill University’s Centre for Intelligent Machines. Although RVS4W is equally useful for design as well as for manufacturing purposes, it is also intended as an educational tool. It combines superb 3-D graphics with a user-friendly window-driven environment. RVS4W can provide quantitative information such as the characteristic length, the maximum reach, the optimum posture and the robot conditioning of a given robot. RVS4W is freeware, open-source and platform-independent. The package is a small-sized stand-alone application which makes it very easy to distribute and install, with no stringent hardware requirements. An elaborate User’s Manual of RVS4W is also available for free downloading. The above-mentioned features make RVS4W a valuable pedagogical tool in robotics.

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)0.001
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 score0.740
Threshold uncertainty score0.610

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.023
GPT teacher head0.211
Teacher spread0.189 · 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

Citations3
Published2011
Admission routes4
Has abstractyes

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