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Record W2763529930 · doi:10.1109/lra.2017.2759789

Cooperative Continuum Robots: Concept, Modeling, and Workspace Analysis

2017· article· en· W2763529930 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Robotics and Automation Letters · 2017
Typearticle
Languageen
FieldEngineering
TopicSoft Robotics and Applications
Canadian institutionsToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsWorkspaceReachabilityRobotComputer scienceMathematical optimizationSimulationControl theory (sociology)MathematicsControl (management)Artificial intelligenceAlgorithm

Abstract

fetched live from OpenAlex

In this letter, we present cooperative continuum robot (CCR) concept, kineto-static analysis, and model validation. Our motivation is to provide increased reachability and maneuverability required in a wide range of continuum robot applications, such as medical interventions. We present a model for the CCR with a minimum number of unknown parameters by formulating the governing equations of each continuum robot in the local frame. The obtained equations are then reformulated in a scaled and nondimensional iterative scheme, leading to a computationally stable and efficient model of the CCR, at rates that enable real-time simulation, design optimization, and control. As a case study, a coupled catheters system is chosen to perform the experimental verifications of the proposed CCR model. Simulations are also conducted to evaluate the enhancement of the workspace and dexterity of the CCR.

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: Empirical · Consensus signal: none
Teacher disagreement score0.831
Threshold uncertainty score0.584

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 head0.013
GPT teacher head0.240
Teacher spread0.227 · 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