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Record W2006780385 · doi:10.1109/icinfa.2013.6720494

Off-line programming of robotic system based on DXF files of 3D models

2013· article· en· W2006780385 on OpenAlexaff
Zhenneng Yin, Yisheng Guan, Shengjun Chen, Wenqiang Wu, Hong Zhang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRobotic Mechanisms and Dynamics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsComputer scienceExecutableTrajectoryOpenGLRobotSoftwareModular designPosition (finance)Coordinate systemLine (geometry)CADComputer graphics (images)Industrial robotComputer visionEngineering drawingArtificial intelligenceProgramming languageVisualizationEngineering

Abstract

fetched live from OpenAlex

For the convenience of complex trajectory programming of robot and in order to enrich robotic off-line programming (OLP) types, this paper presents an efficient robotic OLP method based on DXF files of 3D modeling software. By decoding DXF files, the 3D position information of object graphic elements such as points, lines, arcs and splines are first extracted, all the graphic elements are then converted into point elements. A trajectory planning algorithm is proposed to make these points linked into robot trajectories according to the drawing order in CAD software. Except for the position information of the trajectory, the orientation of the trajectory is also planned by an easy and efficient method. Coordinate transformation is fulfilled by calibration,The planned trajectory is verified with OpenGL simulation, the executable program is then generated and downloaded into the robot controlle. Experiment results of the 5-DoFs modular robot show that the presented OLP system is effective and can be used in practice.

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 score0.706
Threshold uncertainty score0.372

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 head0.013
GPT teacher head0.190
Teacher spread0.177 · 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

Citations10
Published2013
Admission routes1
Has abstractyes

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