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Record W4240681726 · doi:10.1115/1.2803254

The Kinematics of Wheeled Mobile Robots With Dual-Wheel Transmission Units

2007· article· en· W4240681726 on OpenAlexaff
Chao Chen, Svetlana Ostrovskaya, Jorge Angeles

Bibliographic record

VenueJournal of Mechanical Design · 2007
Typearticle
Languageen
FieldEngineering
TopicControl and Dynamics of Mobile Robots
Canadian institutionsMcGill UniversityUniversity of Toronto
Fundersnot available
KeywordsMobile robotRobotKinematicsTrajectoryTransmission (telecommunications)Inverse kinematicsSuspension (topology)Dual (grammatical number)Robot kinematicsComputer scienceMechanism (biology)Control theory (sociology)EngineeringSimulationControl engineeringArtificial intelligenceMathematicsControl (management)Telecommunications

Abstract

fetched live from OpenAlex

The dual-wheel transmission unit, an innovative driving mechanism for wheeled mobile robots, was introduced elsewhere. In this paper, we discuss wheeled mobile robots with such units, supplied with a novel suspension to keep the wheel-ground contact in spite of the irregularities of the floor. We derive closed-form solutions and constraints pertaining to the direct and inverse-kinematics problems of these robots; the constraints reveal the mobility of the robots at hand. Furthermore, we provide an algorithm for the trajectory tracking of the same robots that relies on a novel technique, which is termed the companion-curve method.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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 communication0.0000.001
Open science0.0010.001
Research integrity0.0010.000
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 head0.011
GPT teacher head0.213
Teacher spread0.202 · 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 source (direct Gemma or distilled Codex), 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

Citations5
Published2007
Admission routes1
Has abstractyes

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