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R3VAMPs - Fully Recyclable, Reconfigurable, and Recoverable Vacuum Actuated Muscle-inspired Pneumatic structures

2022· article· en· W4225081784 on OpenAlexafffund
Portia Rayner, Luka Morita, Xiaoruo Sun, Dan Sameoto

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSoft Robotics and Applications
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSoft roboticsActuatorSilicone rubberRobotComputer scienceRoboticsPneumatic actuatorSoft materialsProcess engineeringProcess (computing)Mechanical engineeringControl engineeringEngineeringMaterials scienceArtificial intelligenceNanotechnologyComposite material

Abstract

fetched live from OpenAlex

We present a version of Vacuum Actuated Muscle-Inspired Pneumatic structures (VAMPs) that is entirely constructed of polypropylene to be of potential use in medical, or other single use applications where contamination may occur and where the full lifecycle is considered so that many aspects are recoverable, reusable or otherwise use minimal materials. We title these actuators Recyclable, Reconfigurable and Recoverable VAMPs (R3VAMPs). A traditional material for soft robotics like silicone rubber can last for thousands or millions of actuation cycles, but if it was damaged or otherwise contaminated in a way that prevented easy cleaning it is not easily recyclable or recoverable, and that would be extremely financially and environmentally costly. By constructing our soft robotic structure entirely out of polypropylene, the system may be manufactured from recycled materials and/or recycled after use if needed, without costly material separation requirements. The material costs for soft actuators can be as little as $0.25 and the mechanical design and assembly process can allow the basic system to operate as a joint, a muscle or a bone by combining vacuum operation and variable sleeve properties to actuate or jam the R3VAMPs for different behaviors. As such, this solution provides an extremely low cost and more environmentally benign option to introduce soft robotics into single or few use applications because the system has been designed explicitly with the disposal and recovery requirements in mind.

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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.146
Threshold uncertainty score0.998

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)0.0030.000

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 head0.010
GPT teacher head0.195
Teacher spread0.185 · 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 teacher head, not a consensus.

Study designSimulation or modeling
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

Citations3
Published2022
Admission routes2
Has abstractyes

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