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Record W1963813316 · doi:10.1115/imece2003-41470

DeltaBot: A New Cable-Based Ultra High Speed Robot

2003· article· en· W1963813316 on OpenAlexafffund
Saeed Behzadipour, Robert G. Dekker, Amir Khajepour, Edmon Hok-Man Chan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRobotic Mechanisms and Dynamics
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsInertiaRobotRobot end effectorKinematicsParallel manipulatorComputer scienceMechanism (biology)Robot kinematicsDegrees of freedom (physics and chemistry)EngineeringControl engineeringMechanical engineeringSimulationMobile robotArtificial intelligencePhysics

Abstract

fetched live from OpenAlex

The growing needs for high speed positioning devices in the automated manufacturing industry have been challenged by robotic science for more than two decades. Parallel manipulators have been widely used for this purpose due to their advantage of lower moving inertia over the conventional serial manipulators. Cable actuated parallel robots were introduced in 1980’s to reduce the moving inertia even further. In this work, a new cable-based parallel robot is introduced. For this robot, the cables are used not only to actuate the end-effector but also to apply the necessary kinematic constraints to provide three pure translational degrees of freedom. In order to maintain tension in the cables, a passive air cylinder is used to push the end-effector against the stationary platform. In addition to low moving inertia, the new design benefits from simplicity and low manufacturing cost by eliminating joints from the robot’s mechanism. The design procedure and the results of experiments will be discussed in the following.

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: Methods · Consensus signal: Methods
Teacher disagreement score0.305
Threshold uncertainty score0.999

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)0.0020.000

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 head0.187
Teacher spread0.177 · 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
GenreMethods

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

Citations19
Published2003
Admission routes2
Has abstractyes

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