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Record W4413735309 · doi:10.1017/pds.2025.10136

Design of a Reconfigurable Crawler based on Waterbomb Origami

2025· article· en· W4413735309 on OpenAlexaff
Lingchen Kong, Yaoyao Fiona Zhao

Bibliographic record

VenueProceedings of the Design Society · 2025
Typearticle
Languageen
FieldComputer Science
TopicRobotic Path Planning Algorithms
Canadian institutionsMcGill University
Fundersnot available
KeywordsWeb crawlerComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

ABSTRACT: Inspired by nature, where organisms adapt their shapes to navigate complex challenges, engineering systems can benefit from reconfigurable designs that move beyond rigid, conventional strategies. Reconfiguration offers a promising solution for systems to adapt dynamically to changing operational requirements. Origami, known for its ability to transform from simple 2D sheets into intricate 3D structures, provides a powerful framework for designing adaptable and reconfigurable systems. In this study, a waterbomb origami-based (WOB) crawler is proposed featuring reverse movement without changing actuation. The unfolding and folding process of the WOB enables motion due to the friction between the vertex and the ground, whereas the reverse movement is achieved by leveraging the local bistability of one WOB crease.

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: none
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 science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.027
GPT teacher head0.240
Teacher spread0.213 · 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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