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Record W2499892319 · doi:10.5539/mas.v10n11p54

Investigation on MDOF Bilateral Teleoperation Control System Using Geared DC-Motor

2016· article· en· W2499892319 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
KeywordsTeleoperationTorqueControl theory (sociology)WorkspaceDC motorController (irrigation)Observer (physics)Computer scienceControl systemPosition (finance)Control engineeringSimulationEngineeringControl (management)RobotPhysicsArtificial intelligence

Abstract

fetched live from OpenAlex

This paper presents the research on bilateral teleoperation control system of two link planar manipulator. The bilateral control system consists of 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 common used actuators were linear motors and direct drive DC motor. However, the application of DC motor with gearhead is vast in industry, due to the need for high output force or torque. Thus in this paper, a deeper research on bilateral teleoperation control system is proposed with implementation of gear into the DC-motor. The modelling of multi-degrees-of-freedom (MDOF) bilateral teleoperation control system is designed with the implementation of workspace observer (WOB), reaction force observer (RFOB), position controller and force controller. During the experiments, free motion and contact motion were conducted to validate the proposed setup in bilateral teleoperation control system. The position and torque responses of both master and slave manipulators were observed. The operationality and reproducibility of this proposed system were evaluated through experimental results. Ultimately, this paper focused on the performance of the proposed setup and is analysed by using reproducibility and operationality.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.893
Threshold uncertainty score0.414

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 head0.028
GPT teacher head0.204
Teacher spread0.177 · 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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