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Record W1986658796 · doi:10.1109/icra.2014.6906919

Development of high performance intrinsically safe 3-DOF robot

2014· article· en· W1986658796 on OpenAlexaff
Alex S. Shafer, Mehrdad R. Kermani

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicProsthetics and Rehabilitation Robotics
Canadian institutionsWestern University
Fundersnot available
KeywordsClutchActuatorTorqueRobotComponent (thermodynamics)InertiaControl engineeringComputer scienceWork (physics)Control theory (sociology)EngineeringSimulationAutomotive engineeringMechanical engineeringArtificial intelligenceControl (management)Physics

Abstract

fetched live from OpenAlex

In our previous work we have introduced the Distributed Active/Semi-Active actuation concept. This paper presents the design of a novel three Degrees-of-Freedom (DOF) robot manipulator based on the DASA actuation approach. The robot is developed as a proof-of-concept prototype intended to demonstrate the capacity of the DASA approach to achieve a high degree of interaction safety as well as performance. Magneto-Rheological (MR) clutches form the basis of the Semi-active actuation component, while a unidirectional motor provides the active drive for the robot. An antagonistic clutch configuration is implemented at the joints to achieve bi-directional actuation without reversal of the motor. MR clutches have been shown to exhibit excellent torque-to-inertia and torque-to-mass ratios making them likely candidates for the development of human-safe actuators. In this paper, the safety characteristics of the DASA approach are qualitatively discussed. Experimental results highlighting the performance capability of the developed robot are given.

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: Empirical
Teacher disagreement score0.286
Threshold uncertainty score0.196

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 head0.005
GPT teacher head0.178
Teacher spread0.172 · 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

Citations16
Published2014
Admission routes1
Has abstractyes

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