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Record W2075692480 · doi:10.1115/1.1711822

Conceptual Design and Dimensional Synthesis of a Novel 2-DOF Translational Parallel Robot for Pick-and-Place Operations

2003· article· en· W2075692480 on OpenAlexaff
Tian Huang, Zhanxian Li, Meng Li, D.G. Chetwynd, Clément Gosselin

Bibliographic record

VenueJournal of Mechanical Design · 2003
Typearticle
Languageen
FieldEngineering
TopicRobotic Mechanisms and Dynamics
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsRobotKinematicsConceptual designComputer scienceParallel manipulatorMechanism (biology)SMT placement equipmentControl engineeringSimulationSet (abstract data type)EngineeringArtificial intelligenceHuman–computer interaction

Abstract

fetched live from OpenAlex

This paper deals with the conceptual design and optimal dimensional synthesis of a novel 2-DOF translational parallel robot for pick-and-place operations. In a conceptual design phase, the conditions for generating such kinds of parallel robots are investigated, leading to the invention of a 2-D version of the Delta robot. Combining this robot with a 1-DOF feed mechanism, a hybrid robot can be created which is particularly suitable for transporting objects at very high speed in a plane plus a relatively slow or step-by-step, yet long distance motion, normal to the plane. The kinematic optimality of the 2-DOF translational parallel robot is achieved by minimizing a global and comprehensive conditioning index subject to a set of appropriate constraints. The application of this robot to the development of a device for quality inspection of rechargeable batteries is used to demonstrate its applicability.

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: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.006

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 head0.043
GPT teacher head0.242
Teacher spread0.199 · 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
GenreMethods

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

Citations235
Published2003
Admission routes1
Has abstractyes

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