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Record W2624785266

Enhanced Stability of Three-Users Multirate Distributed Haptic Cooperation via Coordination to Average Peer Position

2011· article· en· W2624785266 on OpenAlexaff
Ramtin Rakhsha, Daniela Constantinescu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTeleoperation and Haptic Systems
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsHaptic technologyPosition (finance)Computer scienceStability (learning theory)Peer-to-peerPosition paperCoordination gameDistributed computingControl theory (sociology)SimulationArtificial intelligenceMathematicsBusinessControl (management)World Wide Web
DOInot available

Abstract

fetched live from OpenAlex

Abstract—Distributed networked haptic cooperation may be-come unstable when the number of interacting users increases because the effective coordination gain for the shared virtual object increases. The average position coordination strategy maintains the coordination gain of the shared virtual object constant regardless of the number of cooperating participants. Therefore, the average position strategy is expected to increase the stability region of networked haptic cooperation among multiple users. This paper confirms through analysis and experiments that AP coordination maintains the three-users haptic cooperation stable for larger coordination gains than traditional virtual coupling coordination. The stability analysis is performed in a multirate control framework. Multirate control is deployed to support high sampling rate of the peer force feedback loops in the presence of a low network update rate. The experiments report a one degree of freedom manipulation of a virtual cube by three cooperating users. Keywords-Networked haptic cooperation; distributed control; multirate control; coordination to averaged position. I.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.543
Threshold uncertainty score0.757

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)0.0010.000

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 head0.023
GPT teacher head0.218
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 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

Citations3
Published2011
Admission routes1
Has abstractyes

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