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Record W2124028049 · doi:10.1109/icra.2011.5980432

A biologically inspired controller for fast eye movements

2011· article· en· W2124028049 on OpenAlex
Martin Lesmana, Dinesh K. Pai

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicGaze Tracking and Assistive Technology
Canadian institutionsUniversity of British Columbia
FundersCanada Research Chairs
KeywordsEye movementSaccadic maskingController (irrigation)Overshoot (microwave communication)Computer scienceOpen-loop controllerControl theory (sociology)Movement (music)Artificial intelligenceEye tracking on the ISSHuman eyeComputer visionNeurophysiologySimulationClosed loopControl engineeringEngineeringNeuroscienceControl (management)PsychologyPhysicsAcoustics

Abstract

fetched live from OpenAlex

We describe and test a non-linear control algorithm inspired by the behavior of motor neurons in humans and other animals during extremely fast saccadic eye movements. The algorithm is implemented on a robotic eye, which includes a stiff camera cable, similar to the optic nerve, which adds a complicated non-linear stiffness to the plant. For high speed movement, our "pulse-step" controller operates open-loop using an internal model of the eye plant learned from past measurements. We show that the controller approaches the performance seen in the human eye, producing fast movements with little overshoot. Interestingly, the controller reproduces the main sequence relationship observed in animal eye movements.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.861
Threshold uncertainty score0.239

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 science0.0010.000
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 head0.048
GPT teacher head0.257
Teacher spread0.209 · 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

Quick stats

Citations10
Published2011
Admission routes2
Has abstractyes

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