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Jonathan Decavel-Bueff

dblp:268/1564 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
1 paper
Wireless sensing and localization · 100%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Wireless sensing and localization
ranging
0.412020
Demo Abstract: Collision Prediction from Pairwise Ranging · IPSN 2020

Methods — techniques the papers use, named apart from their topics

range measurement · 0.4
YearPublicationVenuePosition
2020 Demo Abstract: Collision Prediction from Pairwise Ranging
abstract
The ability to predict, and thus react to, oncoming collisions among a set of mobile agents is a fundamental requirement for safe autonomous movement, both human and robotic. This demonstration tests a pairwise method in which two agents collect repeated range measurements and predict if they will collide. Compared to methods which use GPS or TDOA to track each agent and then predict collisions, this method does not rely on infrastructure or a fixed coordinate system. However, the accurate prediction of future pairwise range, and thus collision prediction, is highly sensitive to noise and changes in velocity. This prototype can be used to provide intuition for the method’s strengths and weaknesses.
Alemayehu Solomon Abrar, Neal Patwari, Jonathan Decavel-Bueff
IPSN3