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Record W1995602033 · doi:10.1109/ccece.2006.277740

Virtual Prototyping for Conceptual Design of a Tracked Mobile Robot

2006· article· en· W1995602033 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicModeling and Simulation Systems
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsVirtual prototypingRobotMobile robotComputer scienceConceptual designTerrainProcess (computing)SimulationSoftwareHuman–computer interactionArtificial intelligence

Abstract

fetched live from OpenAlex

Mobile robots equipped with manipulator arms are often required to operate on rough and uneven terrains. During the design stage, the designer needs to verify the robots performance on various test terrains. Physical prototyping although is more desirable, may prove to be expensive and time consuming. Virtual prototyping can be used especially in the conceptual design stage in order to significantly reduce the amount of physical testing that is required. This paper discusses the application of virtual prototyping using ADAMS software for tracked mobile robots. The virtual prototype was created for an existing robot and was validated with tests done on the physical robot. Different types of virtual terrains were created and dynamic simulations of the robot were performed on these terrains. The simulation results helped in many ways including visualization of the robot motion on different terrains and in determining the limiting dimensions of obstacles, stairs, ditches, etc., that the robot can safely negotiate. The described process can be applied to new robot designs, while still in their conceptual design stage

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.

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 score0.833
Threshold uncertainty score0.224

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 head0.052
GPT teacher head0.276
Teacher spread0.223 · 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

Quick stats

Citations14
Published2006
Admission routes1
Has abstractyes

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