MétaCan
Menu
Back to cohort
Record W2104706738 · doi:10.1109/romoco.2004.240737

Stratified motion planning concept in stair-like environment

2004· article· en· W2104706738 on OpenAlexaff
István Harmati, Béla Lantos, Shahram Payandeh

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicRobotic Path Planning Algorithms
Canadian institutionsSimon Fraser University
FundersMagyar Tudományos AkadémiaHungarian Scientific Research Fund
KeywordsNonholonomic systemHolonomicMotion planningComputer scienceMotion (physics)TrajectoryStair climbingRobotTracking (education)Artificial intelligenceMobile robotControl engineeringEngineering

Abstract

fetched live from OpenAlex

This paper addresses the motion planning of stratified systems (like legged robots) in non-smooth (or called also stair-like) environment and discusses also some limitations. Our earlier works solved trajectory tracking problem in smooth environment if the stratified system is holonomic or the nonholonomic stratified system satisfies the so called decomposed Lie algebra condition (DLARC). The proposed algorithm establishes a concept that integrates these algorithms in order to extend the results for non-smooth (stair-like) environment and to resolve the stair-climbing problem.

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: Methods · Consensus signal: none
Teacher disagreement score0.673
Threshold uncertainty score0.440

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 head0.022
GPT teacher head0.245
Teacher spread0.223 · 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
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

Citations0
Published2004
Admission routes1
Has abstractyes

Explore more

Same topicRobotic Path Planning AlgorithmsFrench-language works237,207