MétaCan
Menu
Back to cohort
Record W2163997125 · doi:10.1109/robot.2005.1570340

Motion Study of an Omni-Directional Rover for Step Climbing

2006· article· en· W2163997125 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicControl and Dynamics of Mobile Robots
Canadian institutionsMcGill University
Fundersnot available
KeywordsMobile robotKinematicsComputer scienceTerrainRobotClimbingSimulationMotion planningRobot kinematicsBogieEngineeringArtificial intelligenceMechanical engineeringGeography

Abstract

fetched live from OpenAlex

In this paper, a study of a wheeled mobile robot (WMR) with omni-directional mobility and rover-like climbing ability is presented. Various rovers with robust locomotion design had been developed. However, the rover locomotion design with omni-directional mobility has not been addressed commonly. Shrimp suspension system and parallel bogies were employed as robot locomotion. It adapts to the terrain profile passively and it has better climbing capability than other rovers. To achieve a singularityless motion, the kinematic model of a wheeled mobile robot (WMR), including a platform equipped with six omni-directional wheels (ODWs), is formulated. The contents of this study are the design principle, kinematics, and motion studies. Also, experimental results have been employed to verify the model developed.

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: Empirical
Teacher disagreement score0.129
Threshold uncertainty score0.236

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 head0.005
GPT teacher head0.202
Teacher spread0.197 · 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

Quick stats

Citations8
Published2006
Admission routes1
Has abstractyes

Explore more

Same topicControl and Dynamics of Mobile RobotsFrench-language works237,207