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Record W2099924624 · doi:10.1109/icra.2011.5980452

Development and testing of a novel high speed SCARA type manipulator for robotic applications

2011· article· en· W2099924624 on OpenAlexafffund
Migara H. Liyanage, Nicholas Krouglicof, Raymond G. Gosine

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHydraulic and Pneumatic Systems
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSCARAActuatorRotary actuatorServomotorControl theory (sociology)ServoElectrohydraulic servo valveController (irrigation)Control engineeringTorqueRobotManipulator (device)Computer scienceGimbalEngineeringMechanical engineeringArtificial intelligenceAerospace engineeringControl (management)Physics

Abstract

fetched live from OpenAlex

This paper proposes using servo hydraulics for high speed robotic manipulation. It details the development of a novel double vane rotary type actuator custom designed for use in a Selective Compliant Assembly Robotic Arm (SCARA). The system, which is mathematically modeled and simulated, consists of an electro-hydraulic servo valve, double vane rotary actuator, manipulator and a controller. Based on the simulation results, hydraulic actuators were sized for optimal performance. A prototype of the proposed manipulator was built and tested. The test results show that the proposed actuator is capable of reaching torques of up to 860 Nm. The end effector of the manipulator is capable of reaching average velocities in excess of 2.7 ms <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup> with a payload capability of 5.3 kg. Comparable performance is not feasible with contemporary SCARA type robots with electric motors.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.708
Threshold uncertainty score0.211

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 head0.108
GPT teacher head0.237
Teacher spread0.129 · 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

Citations11
Published2011
Admission routes2
Has abstractyes

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