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Record W2033792918 · doi:10.1155/2013/683041

Electromechanical Characterization and Locomotion Control of IPMC BioMicroRobot

2013· article· en· W2033792918 on OpenAlexafffund
Martin J.-D. Otis

Bibliographic record

VenueAdvances in Materials Science and Engineering · 2013
Typearticle
Languageen
FieldEngineering
TopicDielectric materials and actuators
Canadian institutionsUniversité du Québec à Chicoutimi
FundersUniversité de Sherbrooke
KeywordsMaterials scienceLaser Doppler vibrometerNafionActuatorLinearityHexapodAcousticsComputer scienceOptoelectronicsElectrodeElectronic engineering

Abstract

fetched live from OpenAlex

This paper presents the electromechanical characterization of Nafion-Pt microlegs for the development of an insect-like hexapod BioMicroRobot (BMR). BMR microlegs are built using quasi-cylindrical Nafion-Pt ionomeric polymer-metal composite (IPMC), which has 2.5 degrees of freedom. The specific manufacturing process using a laser excimer for one leg in three-dimensional configurations is discussed. Dynamic behavior and microleg characteristics have been measured in deionized water using a laser vibrometer. The use of the laser vibrometer shows the linear characteristics between the duty cycle of square wave input and displacement rate of the actuator at multiple frequencies. This linearity is used to design a servo-system in order to reproduce insect tripod walking. As well, BMR current consumption is an important parameter evaluated for each leg. Current passing throughout the IPMC membrane can result in water electrolysis. Four methods are explained for avoiding electrolysis. The hardware test bench for measurements is presented. The purpose of this design is to control a BMR for biomedical goals such as implantation into a human body. Experimental results for the proposed propulsion system are conclusive for this type of bioinspired BMR.

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 score0.003

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 communication0.0000.000
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 head0.002
GPT teacher head0.174
Teacher spread0.172 · 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

Citations8
Published2013
Admission routes2
Has abstractyes

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