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Record W2156644041 · doi:10.1109/icarcv.2006.345413

The Dynamic Analysis of a Planar Parallel Manipulator with Joint-Coupling

2006· article· en· W2156644041 on OpenAlexaff
Theingi, I‐Ming Chen, Chuan Li, Jorge Angeles

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRobotic Mechanisms and Dynamics
Canadian institutionsMcGill University
Fundersnot available
KeywordsControl theory (sociology)Coupling (piping)TorquePlanarJoint (building)TrajectoryActuatorComputer sciencePower (physics)Limit (mathematics)Control engineeringEngineeringMathematicsPhysicsControl (management)Structural engineeringMechanical engineeringMathematical analysisArtificial intelligence

Abstract

fetched live from OpenAlex

In this paper, the dynamics of planar parallel manipulators with joint-coupling is presented. In the manipulator with joint-coupling, the actuator torques are distributed among the coupled joints. Hence, the dynamic behavior of the manipulator and the trajectory planning will be different from those manipulators without joint-coupling. Furthermore, the coupling coefficients of the joint-coupling provide an additional way to adjust the dynamic performance of the manipulator. Because of joint-coupling, the total power consumption along the desired trajectory becomes a function of the coupling coefficients. With a maximum limit on the motor torque output, it is possible to find an appropriate set of coupling coefficients that minimize the total power consumption

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 score0.003
Threshold uncertainty score0.008

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 studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
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 head0.006
GPT teacher head0.182
Teacher spread0.176 · 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
Published2006
Admission routes1
Has abstractyes

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