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Record W2060076231 · doi:10.1115/detc2009-86713

Modeling, Control and Simulation of a New Large Scale Cable-Driven Robot

2009· article· en· W2060076231 on OpenAlexaff
Alireza Alikhani, Saeed Behzadipour, Farbod Ghahremani, Aria Alasty, Seyed Ali Sadough Vanini

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSoft Robotics and Applications
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsRobotKinematicsActuatorMechanism (biology)LinearizationRoboticsComputer scienceFeedback linearizationControl engineeringTorqueRobot kinematicsControl theory (sociology)Motion controlScale (ratio)SimulationControl (management)EngineeringArtificial intelligenceMobile robotNonlinear systemPhysics

Abstract

fetched live from OpenAlex

In this paper, modeling and control of a new cable-driven robot is presented. In this mechanism, the cable arrangement eliminates the rotational motions leaving the moving platform with three translational motion. The mechanism has potentials for large scale manipulation and robotics in harsh environments. In this article kinematics and dynamics models for the proposed cable-driven architecture are derived. Additionally, Feedback linearization under input constraints is used for the control of the robot. The control algorithm ensures the cable tensions are positive while minimizing the sum of all the torques exerted by the actuators. Finally, the implementation of the proposed method is demonstrated through simulation.

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 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 score0.934
Threshold uncertainty score0.169

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 head0.011
GPT teacher head0.240
Teacher spread0.229 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations4
Published2009
Admission routes1
Has abstractyes

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