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Record W2159136263 · doi:10.1109/robot.2006.1642145

Discrete-time multi-model control for cooperative teleoperation under time delay

2006· article· en· W2159136263 on OpenAlexaff
Peyman Setoodeh, Shahin Sirouspour, Ali Shahdi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTeleoperation and Haptic Systems
Canadian institutionsMcMaster University
Fundersnot available
KeywordsTeleoperationControl theory (sociology)Linear-quadratic-Gaussian controlComputer scienceRobustness (evolution)RobotDiscrete time and continuous timeTeleroboticsParametric statisticsControl engineeringEngineeringMobile robotControl (management)MathematicsArtificial intelligence

Abstract

fetched live from OpenAlex

While a conventional bilateral teleoperation system involves only one pair of master/slave robots, cooperative telerobotic systems can consist of multiple pairs of robotic manipulators. Due to dynamic interaction among slave manipulators as well as communication latency, the control of such systems can be particularly challenging. This paper presents a multimodel discrete-time controller for teleoperation in cooperative environments subject to a known constant communication delay. Discrete-time state-space models that explicitly incorporate signal delays are developed for free motion/soft contact and rigid contact phases of teleoperation. Mode-based linear quadratic Gaussian (LQG) controllers are proposed that can deliver a stable transparent response for each phase of operation. Switching among these controllers occur according to the identified phase of contact. The robustness of the controllers with respect to parametric uncertainty is examined via the Nyquist analysis. Simulation results demonstrate the effectiveness of the proposed approach

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: Methods · Consensus signal: none
Teacher disagreement score0.968
Threshold uncertainty score0.786

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)0.0000.001

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 head0.009
GPT teacher head0.221
Teacher spread0.212 · 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
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

Citations17
Published2006
Admission routes1
Has abstractyes

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