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Record W4416020268 · doi:10.1016/j.procs.2025.10.138

Design, Modeling and Experimental Investigation for a Helix-based Cable-Driven Soft Continuum Robot

2025· article· en· W4416020268 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueProcedia Computer Science · 2025
Typearticle
Languageen
FieldEngineering
TopicSoft Robotics and Applications
Canadian institutionsDalhousie University
FundersNatural Science Foundation of Zhejiang ProvinceNational Natural Science Foundation of China
KeywordsRobotKinematicsCurvatureAdaptabilityConstant curvatureFeed forwardConstant (computer programming)Control theory (sociology)

Abstract

fetched live from OpenAlex

Soft continuum robots have gained significant attention in various applications due to their inherent compliance and adaptability to complex environments. In this paper, a Helix-based Cable-Driven Soft continuum Robot (HCDSR) is proposed with the corresponding modeling established and experimental validation conducted. The proposed robot features a helix-based structure that enables direct 3D printing manufacturing as a monolithic unit, substantially reducing assembly requirements and improving structural consistency. The constant curvature assumption-based kinematic model is applied to characterize the robot’s deformation behavior, which has the potential to serve as an effective feedforward control law to enhance dynamic performance. Experimental investigations demonstrate that the constant curvature assumption remains valid within a specified curvature range, confirming its applicability for both modeling and control purposes. The results validate the effectiveness of the proposed design approach and modeling framework, providing a foundation for practical implementation of helix-based soft continuum robots in various applications.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.600
Threshold uncertainty score0.362

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)0.0000.000

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 head0.248
Teacher spread0.225 · 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