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Record W1936189409 · doi:10.1109/robot.1989.100202

Kinematics and dynamics of a three-wheeled 2-DOF AGV

2003· article· en· W1936189409 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicControl and Dynamics of Mobile Robots
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsKinematicsNonholonomic systemConstraint (computer-aided design)Kinematics equationsComputer scienceComplement (music)Euler anglesOrthogonal complementControl theory (sociology)Motion (physics)Equations of motionRobot kinematicsRobotControl engineeringMathematicsArtificial intelligenceMobile robotControl (management)EngineeringClassical mechanicsGeometryPhysics

Abstract

fetched live from OpenAlex

A systematic method for the kinematic and dynamic modeling of a two-degree-of-freedom (DOF) automatic guided vehicle (AGV) is presented. This type of methodology can be used to analyze, design, simulate, and control any kind of rolling robots. The concept of orthogonal complement is used to develop the dynamical equations of motion. The vehicle is analyzed for simulation purposes. Simulation results are reported. It is shown that, using the natural orthogonal complement of the matrix of velocity constraint equations, it is possible to derive systematically the Euler-Lagrange equations of motion of nonholonomic robotic mechanical systems. Moreover, the introduction of the orthogonal complement leads naturally to an efficient computational algorithm.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.673
Threshold uncertainty score0.323

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 head0.004
GPT teacher head0.173
Teacher spread0.168 · 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

Citations51
Published2003
Admission routes2
Has abstractyes

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