MétaCan
Menu
Back to cohort
Record W2003715139 · doi:10.1109/icra.2014.6907835

Effect of normal force dispersion on the mobility of wheeled robots operating on soft soil

2014· article· en· W2003715139 on OpenAlexaff
Bahareh Ghotbi, Francisco González, József Kövecses, Jorge Angeles

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSoil Mechanics and Vehicle Dynamics
Canadian institutionsMcGill University
Fundersnot available
KeywordsTerrainRobotTraction (geology)Computer scienceNormal forceTractive forceSimulationMobile robotContact forceDispersion (optics)Aerospace engineeringEngineeringMechanical engineeringArtificial intelligencePhysicsMechanics

Abstract

fetched live from OpenAlex

A number of applications of wheeled robots, including planetary exploration rovers and rescue missions, require that the vehicle operates in a non-structured environment. Optimizing the vehicle mobility is of key importance in such applications. Reduced mobility can limit the ability of the robot to achieve the mission goals, or even render it immobile in extreme cases. In this paper, the effect of normal contact forces on mobility is reported. A performance indicator based on the force distribution is defined and used to compare different vehicle configurations. The validity of this indicator was assessed using both simulation and experimental results obtained for a six-wheel rover prototype. Results suggest that modifying the robot configuration to alter the normal force distribution can lead to increased traction force available at the wheel-terrain interfaces, thus improving the mobility.

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)0.001
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 score0.124
Threshold uncertainty score0.254

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.004
GPT teacher head0.198
Teacher spread0.194 · 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

Citations5
Published2014
Admission routes1
Has abstractyes

Explore more

Same topicSoil Mechanics and Vehicle DynamicsFrench-language works237,207