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Record W2323461888 · doi:10.7210/jrsj.25.618

Dynamic Simulator of Mechanisms Based on the Tangent and Cotangent Vectors

2007· article· en· W2323461888 on OpenAlexfundno aff
Koichi Sugimoto, Hadi T. Nia

Bibliographic record

VenueJournal of the Robotics Society of Japan · 2007
Typearticle
Languageen
FieldEngineering
TopicRobotic Mechanisms and Dynamics
Canadian institutionsnot available
FundersCanadian Institute for Advanced Research
KeywordsTrigonometric functionsKinematicsTangentDirection cosineProperty (philosophy)Tangent vectorMechanism (biology)Euler anglesGeneralized coordinatesControl theory (sociology)Computer scienceExpression (computer science)Screw theoryStewart platformMathematical analysisSimulationMathematicsClassical mechanicsGeometryPhysicsArtificial intelligence

Abstract

fetched live from OpenAlex

The dynamics after that of the Newton-Euler method uses the symmetric property between a momentum vector and a velocity vector, or between a force vector and a velocity vector. The usage of the symmetric property makes the expression of the kinematic and dynamic analysis independent from the choice of a coordinates system. In this paper, it is clarified that this concept can be applied to the analysis of multi-rigid-body systems and mechanisms, using the concept of tangent and cotangent vectors based on the screw coordinates of joint axes. And the procedures of analyses of the closed loop mechanisms and parallel mechanisms are derived. An outline of the algorithm of the simulator for closed loop mechanism and parallel mechanisms is also described and the simulation results of parallel mechanisms are illustrated.

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)0.001
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 score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.008
GPT teacher head0.205
Teacher spread0.197 · 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

Citations0
Published2007
Admission routes1
Has abstractyes

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Same venueJournal of the Robotics Society of JapanSame topicRobotic Mechanisms and DynamicsFrench-language works237,207