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Record W2142878915 · doi:10.1109/toh.2012.73

A Passivity Criterion for Sampled-Data Bilateral Teleoperation Systems

2012· article· en· W2142878915 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Haptics · 2012
Typearticle
Languageen
FieldEngineering
TopicTeleoperation and Haptic Systems
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPassivityTeleoperationControl theory (sociology)TeleroboticsDiscretizationControl engineeringRobotController (irrigation)Stability (learning theory)EngineeringComputer scienceSimulationControl (management)Artificial intelligenceMobile robotMathematics

Abstract

fetched live from OpenAlex

A teleoperation system consists of a teleoperator, a human operator, and a remote environment. Conditions involving system and controller parameters that ensure the teleoperator passivity can serve as control design guidelines to attain maximum teleoperation transparency while maintaining system stability. In this paper, sufficient conditions for teleoperator passivity are derived for when position error-based controllers are implemented in discrete-time. This new analysis is necessary because discretization causes energy leaks and does not necessarily preserve the passivity of the system. The proposed criterion for sampled-data teleoperator passivity imposes lower bounds on the teleoperator's robots dampings, an upper bound on the sampling time, and bounds on the control gains. The criterion is verified through simulations and experiments.

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.

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: none
Teacher disagreement score0.969
Threshold uncertainty score0.746

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 communication0.0000.001
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 head0.076
GPT teacher head0.282
Teacher spread0.205 · 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