MétaCan
Menu
Back to cohort
Record W2114635861 · doi:10.1109/haptic.2012.6183779

Distributed haptic cooperation with passive multirate wave communications

2012· article· en· W2114635861 on OpenAlexafffund
Ramtin Rakhsha, Daniela Constantinescu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTeleoperation and Haptic Systems
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComputer scienceHaptic technologyTransmission (telecommunications)Object (grammar)Constant (computer programming)Distributed computingStability (learning theory)Telecommunications networkTopology (electrical circuits)Computer networkSimulationTelecommunicationsEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

This paper investigates the use of passive multirate wave communications for distributed haptic cooperation between two users connected over a network with constant delay and low transmission rate. The paper develops the lifted state space model of the haptic cooperation system and uses it to compute the maximum stable gains for the users' feedback loops and for the coordination of the virtual object distributed across the network. The multirate stability analysis predicts that: an order of magnitude larger coordination gains can be used when the two users are connected via passive wave communications than when they are connected via powerdomain communications or via traditional wave-domain communications; the maximum coordination gain stays unaffected by constant and symmetric network delays. A larger maximum coordination gain independent of the network delays provides increased and robust coherency of the shared virtual object. Experiments in which two users manipulate a shared virtual cube together validate the multirate stability analysis.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.828
Threshold uncertainty score0.275

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 head0.223
Teacher spread0.195 · 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
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

Citations4
Published2012
Admission routes2
Has abstractyes

Explore more

Same topicTeleoperation and Haptic SystemsFrench-language works237,207