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Record W2302995455 · doi:10.1115/detc2010-28263

Performance Mapping and Motion Simulation of a 4UPS+PU Redundantly Actuated Parallel Manipulator

2010· article· en· W2302995455 on OpenAlexaff
Zhen Gao, Dan Zhang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRobotic Mechanisms and Dynamics
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsWorkspaceParallel manipulatorKinematicsComputer scienceControl theory (sociology)Translation (biology)Inverse kinematicsDiscretizationMotion (physics)Position (finance)Base (topology)Inverse dynamicsMotion controlSimulationRobotArtificial intelligenceMathematicsControl (management)PhysicsMathematical analysis

Abstract

fetched live from OpenAlex

In this paper, a new 4UPS+PU redundantly actuated parallel manipulator is proposed. This mechanism possesses three degrees of freedom (DOF), one translation and two rotations. Different from general parallel manipulators, a passive leg is connected to both centers of the base and the moving platform to constrain the unwanted motion. The mobility study and inverse kinematic analysis are conducted. The reachable workspace is generated with boundary-searching based discretization method. The local and global performance indices including stiffness and dexterity and their atlas are investigated in details. Comprehensive simulation of kinematics, dynamics and proportional-integral-derivative (PID) position control are implemented based on Adams to evaluate and testify the high operational capacity and well motion characteristics.

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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

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 communication0.0000.000
Open science0.0000.000
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 head0.012
GPT teacher head0.202
Teacher spread0.189 · 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

Citations4
Published2010
Admission routes1
Has abstractyes

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