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Record W1664478978

TOWARDS AUTONOMOUS LONG-RANGE NAVIGATION

2005· article· en· W1664478978 on OpenAlexaboutno aff
Érick Dupuis, Pierre Allard, Joseph Nsasi Bakambu, Tom Lamarche, Wen-Hong Zhu, Ioannis Rekleitis

Bibliographic record

VenueESASP · 2005
Typearticle
Languageen
FieldComputer Science
TopicRobotic Path Planning Algorithms
Canadian institutionsnot available
Fundersnot available
KeywordsMars Exploration ProgramTerrainPlanetary explorationExploration of MarsRoboticsMars roverComputer scienceMotion planningSystems engineeringMobile robotMission control centerSoftwareRange (aeronautics)AeronauticsArtificial intelligenceEngineeringRobotAerospace engineeringGeographyAstrobiologyCartography
DOInot available

Abstract

fetched live from OpenAlex

The recent success of NASA’s Mars Exploration Rovers has demonstrated the important benefits that mobility adds to landed planetary exploration missions. The Canadian Space Agency (CSA) has been conducting research in ground control and in autonomous robotics for several years already. One of the target applications is planetary exploration using mobile platforms. The emphasis of our research program is on reactive on-board autonomy software and long-range rover navigation. This paper describes recent activities of the CSA in this area. Key results are described in the areas of terrain modelling, path planning and rover guidance.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.002

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 head0.018
GPT teacher head0.262
Teacher spread0.245 · 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 source (direct Gemma or distilled Codex), 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

Citations20
Published2005
Admission routes1
Has abstractyes

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Same venueESASPSame topicRobotic Path Planning AlgorithmsFrench-language works237,207