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Record W2138584260 · doi:10.1109/irds.2002.1041386

An architecture for a VLSI sensory-motor system for autonomous robots

2003· article· en· W2138584260 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Memory and Neural Computing
Canadian institutionsConcordia University
Fundersnot available
KeywordsPixelComputer scienceVery-large-scale integrationRobotArtificial intelligenceObstacle avoidanceComputer visionSensory systemRoboticsMotion planningMobile robotEmbedded systemNeuroscience

Abstract

fetched live from OpenAlex

An architecture for a VLSI sensory-motor system is presented. It makes use of ideas from behavior-based robotics and biology to achieve an obstacle avoidance behavior in an unstructured environment. Sensory-motor coordination is achieved by correlating a map of the visual field with a map which represents the robot's body. Rapid decision making is facilitated by a post-receptor foveation scheme which permits the fixation of the open pathway and the localization of obstacles through spatial gradients. The foveation scheme uniquely combines space-variant processing with the possibility for high-resolution, per-pixel spatio-temporal operations across the focal plane. Only a small number of computationally simple operations are used per-pixel, potentially leading to implementations with small pixels and high fill-factors.

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: none
Teacher disagreement score0.805
Threshold uncertainty score0.504

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 head0.018
GPT teacher head0.247
Teacher spread0.230 · 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

Citations1
Published2003
Admission routes1
Has abstractyes

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