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Record W2145663347 · doi:10.1109/robot.2008.4543228

Ultrasonic relative positioning for multi-robot systems

2008· article· en· W2145663347 on OpenAlexaff
Frédérik Rivard, Jonathan Bisson, François Michaud, Dominic Létourneau

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicIndoor and Outdoor Localization Technologies
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsBeaconUltrasonic sensorRobotPositioning systemMobile robotComputer sciencePosition (finance)AcousticsReal-time computingSimulationComputer visionArtificial intelligencePhysics

Abstract

fetched live from OpenAlex

Coordination of a group of mobile robots is facilitated when they are able to determine their positions relative to each other. Instead of using an absolute positioning approach with fixed beacons in the operating environment, we have developed a ultrasonic relative positioning system that allows each robot to perceive the distance and the angle of other nearby robots in relation to its own position. The system is based on time-of-flight evaluation of ultrasonic pulses and a RF communication link. The system has a precision of 8 mm and of 3deg over a 6.7 m range. This paper describes the system, its performance and its use on four Pioneer 2 robots moving in formation.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.002

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 head0.038
GPT teacher head0.242
Teacher spread0.205 · 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 designBench or experimental
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

Citations63
Published2008
Admission routes1
Has abstractyes

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