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Record W2790303497 · doi:10.1162/pres_a_00293

FPAA-Based Control of Bilateral Teleoperation Systems for Enhanced User Task Performance

2017· article· en· W2790303497 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

VenuePRESENCE Virtual and Augmented Reality · 2017
Typearticle
Languageen
FieldEngineering
TopicTeleoperation and Haptic Systems
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsTeleoperationController (irrigation)Task (project management)Computer scienceField-programmable analog arrayStability (learning theory)Control theory (sociology)Control engineeringControl (management)SimulationEngineeringComputer hardwareArtificial intelligenceAnalog signal

Abstract

fetched live from OpenAlex

In a bilateral teleoperation system, discrete-time implementation of the controller can cause performance degradation. This is due to a well-known stability-imposed upper bound on the product of the discrete-time controller's gain and the sampling period. In this article, for a bilateral teleoperation system, a continuous-time controller based on a Field Programmable Analog Array (FPAA) is deployed and compared in terms of performance with its discrete-time counterpart. Experimental results show that, unlike the discrete-time controller, the FPAA-based controller helps the human user complete teleoperation tasks that require high controller gains such as when a large impedance needs to be displayed against the user's hand. Also, an experimental object stiffness discrimination study shows that large sampling periods, necessitating low control gains for maintaining stability, lead to unacceptable task performance by the user; however, the users show an improved ability to discriminate the various objects if the teleoperation controller is implemented using an FPAA.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.704
Threshold uncertainty score0.432

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 head0.019
GPT teacher head0.249
Teacher spread0.229 · 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