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Record W1982682728 · doi:10.1109/ccece.2010.5575184

Parking control of an active-joint center-articulated mobile robot based on feedback from beacons

2010· preprint· en· W1982682728 on OpenAlexaff
Mehdi Delrobaei, Kenneth McIsaac

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldComputer Science
TopicRobotic Path Planning Algorithms
Canadian institutionsWestern University
Fundersnot available
KeywordsBeaconMobile robotRobotComputer scienceOrientation (vector space)Robot kinematicsKinematicsPosition (finance)Control theory (sociology)Robot controlControl (management)Control engineeringArtificial intelligenceEngineeringReal-time computingMathematics

Abstract

fetched live from OpenAlex

The paper addresses autonomous parking control of an active-joint center-articulated mobile robot. We first propose a kinematic model of the robot and then a proper law is derived to stabilize the configuration of the vehicle to a small neighborhood of the goal. The control law is designed by Lyapunov techniques and relies on the equations of the robot in polar coordinates. A beacon-based guidance system also provides feedback from the position and orientation of the target. Simulation results show the robots ability to start from any arbitrary position and orientation, and achieve successful parking.

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 categoriesMeta-epidemiology (narrow)
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 score0.574
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0010.001
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 head0.021
GPT teacher head0.257
Teacher spread0.236 · 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

Citations1
Published2010
Admission routes1
Has abstractyes

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