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Record W2022606637 · doi:10.1115/1.4000313

Dynamic Modeling and Analysis of a Circular Track-Guided Tripod

2009· article· en· W2022606637 on OpenAlexaff
Yuwen Li, Fengfeng Xi, Allan Daniel Finistauri, Kamran Behdinan

Bibliographic record

VenueJournal of Computational and Nonlinear Dynamics · 2009
Typearticle
Languageen
FieldEngineering
TopicRobotic Mechanisms and Dynamics
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsTripod (photography)KinematicsActuatorWorkspaceControl theory (sociology)EngineeringFuselageRobotSimulationComputer scienceMechanical engineeringPhysicsClassical mechanicsArtificial intelligence

Abstract

fetched live from OpenAlex

To enlarge the workspace and improve the motion capability of a parallel robot, the base of the robot can be guided to move along a linear or curved track. This paper aims at analyzing how the motion of the base affects the dynamics of a parallel robot. For this purpose, kinematic and dynamic equations are developed for a circular track-guided tripod parallel robot. For kinematics, the motion of the base is incorporated into the analytical formulations of the position and velocity of the tripod. For dynamics, equations of motion are derived using the Lagrangian formulation, and influence factors are defined to provide a quantitative means to measure the effects of the velocity and acceleration of the base on the actuator forces of the tripod. As an application of the above method, a circular track-guided tripod is proposed for the automatic riveting in the assembly of an aircraft fuselage. Simulation studies are carried out to investigate the tripod dynamics. It is found that the motion of the base has a strong impact on the actuator forces. The dynamic model provides a useful tool for the design and control of the circular track-guided tripod.

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: Empirical · Consensus signal: none
Teacher disagreement score0.276
Threshold uncertainty score0.428

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 head0.010
GPT teacher head0.240
Teacher spread0.230 · 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
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

Citations12
Published2009
Admission routes1
Has abstractyes

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