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Miniature Dielectric Elastomer Actuator Probe Inspecting Confined Spaces Embedding a CMOS Sensor

2025· article· en· W4413925241 on OpenAlexaff
Ang Li, Codrin Tugui, Mihai Duduta

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsActuatorElastomerMaterials scienceEmbeddingDielectricCMOSTactile sensorOptoelectronicsElectronic engineeringElectrical engineeringAcousticsComposite materialComputer scienceEngineeringRobotPhysicsArtificial intelligence

Abstract

fetched live from OpenAlex

Navigating and inspecting confined space is crucial for the aerospace and healthcare industries. Exploring smaller and narrower spaces allows for problems to be identified earlier, preventing negative outcomes for patients and equipment. The challenge is to scale down the navigation probe while preserving degrees of freedom (DOF) and functionality. Dielectric elastomer actuators (DEAs) are promising probe candidates because they are solid-state, electrical-driven, and can be scaled down favorably. This work demonstrates a modular 2-DOF DEA miniature probe with an embedded CMOS sensor for visual data acquisition. The modularity achieved by a novel connector system enables switching between single and dual DEA probes based on 2D or 3D pathway structures. The probes can be controlled using a pocket-sized circuit with two knobs to turn. We present the operating mechanism, device assembly, fabrication, and characterization of DEA bending actuators with widths below 2 mm. In the end, we demonstrate the ability of devices to navigate through various complex and confined pathways.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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 communication0.0000.001
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 head0.007
GPT teacher head0.239
Teacher spread0.232 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2025
Admission routes1
Has abstractyes

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