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Record W2502309077 · doi:10.5539/mas.v10n11p98

Investigation on Standardization of Modal Space by Ratio for MDOF Micro-Macro Bilateral Teleoperation Control System

2016· article· en· W2502309077 on OpenAlexvenueno aff
Jun Wei Lee, Zaki bin Hj Shukor Ahmad, Herman bin Jamaluddin Muhammad

Bibliographic record

VenueModern Applied Science · 2016
Typearticle
Languageen
FieldEngineering
TopicTeleoperation and Haptic Systems
Canadian institutionsnot available
FundersUniversiti Teknikal Malaysia Melaka
KeywordsTeleoperationMacroTorqueControl theory (sociology)Computer scienceDC motorActuatorSimulationControl engineeringRobotControl (management)EngineeringArtificial intelligencePhysics

Abstract

fetched live from OpenAlex

This paper presents the research on micro-macro bilateral teleoperation control system of two ink planar manipulator. The micro-macro bilateral control system consists of different size between master and slave system using geared DC-motor. Both master and slave manipulators are actuated by DC-Micromotor attached to planetary gearhead to increase the output torque. In the previous researches the most common actuators used were linear motor and direct-drive DC motors. However, the application of DC motor with gearhead are vast in industry, which need high output force or torque. Thus in this paper, research on micro-macro bilateral teleoperation control system is proposed with the use of gear with the DC-motor. The micro-macro bilateral teleoperation control system provides the human operator with a sense of feel to a micro or macro environment as if it is in the same scale environment. Thus a standardization method is proposed to achieve micro-macro bilateral teleoperation control system. During the experiment, experiment on free motion and contact motion are conducted to validate the proposed setup in bilateral teleoperation control system. The position and torque responses of both master and slave manipulators are observed. The operationality and reproducibility of this proposed system are evaluated through proposed experimental results.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.833
Threshold uncertainty score0.409

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 head0.010
GPT teacher head0.194
Teacher spread0.184 · 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 designBench or experimental
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

Citations1
Published2016
Admission routes1
Has abstractyes

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