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Record W2162552936 · doi:10.1115/1.3023137

Wireless Swimming Microrobot: Design, Analysis, and Experiments

2008· article· en· W2162552936 on OpenAlexaff
Yongshun Zhang, Guangjun Liu

Bibliographic record

VenueJournal of Dynamic Systems Measurement and Control · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMicro and Nano Robotics
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsPropulsionWirelessFinRobotRange (aeronautics)Power (physics)Power consumptionHead (geology)SimulationComputer scienceAcousticsEngineeringMarine engineeringMechanical engineeringAerospace engineeringPhysicsArtificial intelligenceTelecommunicationsGeology

Abstract

fetched live from OpenAlex

This paper presents a bidirectional wireless swimming microrobot that has been developed, analyzed, and experimentally tested. The robot is developed based on fin beating propulsion, using giant magnetostrictive films for head and tail fins. An innovative drive approach, using separate second order resonance frequencies of the head and tail fins to generate forward and backward thrusts, is proposed and implemented on a bidirectional swimming microrobot prototype. Dynamic model of the proposed microrobot has been derived based on theoretical analysis. Simulation and experimental results have demonstrated the feasibility of the proposed drive approach and design. The developed swimming microrobot features a low driving frequency, low power consumption, and a large range of swimming speed in both the forward and backward directions.

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)0.001
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 score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.023
GPT teacher head0.226
Teacher spread0.203 · 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

Citations12
Published2008
Admission routes1
Has abstractyes

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