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Record W2068705067 · doi:10.1109/tsmcb.2005.861878

A control scheme for stable force-reflecting teleoperation over IP networks

2006· letter· en· W2068705067 on OpenAlexaff
Ilia G. Polushin, Peter Liu, Chung–Horng Lung

Bibliographic record

VenueIEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) · 2006
Typeletter
Languageen
FieldEngineering
TopicTeleoperation and Haptic Systems
Canadian institutionsCarleton University
Fundersnot available
KeywordsTeleoperationControl theory (sociology)TrajectoryChannel (broadcasting)Discontinuity (linguistics)Stability (learning theory)Computer scienceScheme (mathematics)Small-gain theoremFilter (signal processing)Function (biology)MathematicsControl (management)TelecommunicationsMathematical analysis

Abstract

fetched live from OpenAlex

The problem of force-reflecting teleoperation over Internet protocol networks is addressed. The existence of time-varying communication delay and the possibility of data losses are taken into consideration. Since significant data loss may result in discontinuity of the reference trajectory transmitted through the communication channel, the proposed control scheme includes a filter that provides a smooth approximation of a possibly discontinuous reference trajectory. The stability of the overall system is guaranteed by a version of the input-to-output stable small-gain theorem for functional differential equations. If the communication delay in the forward channel is an "approximately smooth" function of time, the proposed scheme guarantees that the slave manipulator tracks the delayed trajectory of the master within a prescribed small error.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.231
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 source (direct Gemma or distilled Codex), 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

Citations88
Published2006
Admission routes1
Has abstractyes

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