MétaCan
Menu
Back to cohort
Record W2119728841 · doi:10.1109/tim.2008.919874

Projection-Based Force Reflection Algorithm for Stable Bilateral Teleoperation Over Networks

2008· article· en· W2119728841 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 Instrumentation and Measurement · 2008
Typearticle
Languageen
FieldEngineering
TopicTeleoperation and Haptic Systems
Canadian institutionsCarleton University
Fundersnot available
KeywordsTeleoperationControl theory (sociology)Stability (learning theory)Observer (physics)Reflection (computer programming)SIGNAL (programming language)Computer scienceProjection (relational algebra)StiffnessAlgorithmRobotEngineeringArtificial intelligenceControl (management)Physics

Abstract

fetched live from OpenAlex

The problem of stable force-reflecting teleoperation is addressed, where the communication between the master and the slave is subject to multiple time-varying, discontinuous, and possibly unbounded communication delays. A new force reflection (FR) algorithm is proposed, which improves the stability of the system without decreasing its transparency. Based on the estimate of human forces provided by the high-gain input observer, the proposed algorithm restricts the reflected force in such a way that it eliminates the motion of the master induced by the FR signal without changing the human perception of the environmental force. It is shown that the proposed FR algorithm allows us to achieve stability of the system for an arbitrarily high FR gain and arbitrarily low damping and stiffness of the master manipulator. The stability analysis is based on the input-to-output stability small-gain theorem for systems with multiple time-varying communication delays.

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 score0.953
Threshold uncertainty score0.681

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 head0.040
GPT teacher head0.244
Teacher spread0.204 · 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