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Pierre Marché

dblp:49/6474 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2001
—ORCID · none

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

Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1Graphics, computer vision, multimedia, augmented reality and games · 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.

Artificial intelligence
1 paper
Robot navigation and mapping · 67% 3D vision · 33%
Computer networks
1 paper
Wireless sensing and localization · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot navigation and mapping › robot mapping
environment modeling
0.012001
Quick Primitives Extraction Using Inertia Matrix on Measures Issue from an Ultrasonic Network · ICRA 2001
Robotics › Robot navigation and mapping
map building
0.012001
Quick Primitives Extraction Using Inertia Matrix on Measures Issue from an Ultrasonic Network · ICRA 2001
Computer vision › 3D vision › 3d scene understanding
primitive detection
0.012001
Quick Primitives Extraction Using Inertia Matrix on Measures Issue from an Ultrasonic Network · ICRA 2001
Wireless sensing and localization › acoustic sensing
ultrasonic sensing
0.012001
Quick Primitives Extraction Using Inertia Matrix on Measures Issue from an Ultrasonic Network · ICRA 2001

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

inertia matrix · 0.1hough transform · 0.1
YearPublicationVenuePosition
2001 Quick Primitives Extraction Using Inertia Matrix on Measures Issue from an Ultrasonic Network
abstract
An autonomous mobile robot needs externals sensors for its own localization and modeling environment. In order to perform the angular precision of ultrasonic sensor and to improve the number of informations for a given time, we developed an ultrasonic sensor network using the multiple receivers mode. In this paper we introduce the ultrasonic network with its hardware architecture and its functioning mode. We also present a method to localize an echo source with the multiple receivers mode and show how to simply model this echo in the robot frame. We then describe the extraction of environment primitives (segment) by the inertia matrix and Hough transform. Finally, we validate the all process by experiments.
Joseph Canou, Cyril Novales, Gérard Poisson, Pierre Marché
ICRA4
1999 Geodesic Path Based Interpolation Using Level Sets Propagation
Bruno Migeon, Fabien Boissé, Philippe Deforge, Pierre Marché
CAIP4