Dense RGB-D mapping of large scale environments for real-time localisation and autonomous navigation

Maxime Meilland 1 Patrick Rives 2 Andrew Comport 3
1 AROLAG - Advanced Image Understanding and Autonomous Systems
CRISAM - Inria Sophia Antipolis - Méditerranée
2 Lagadic - Visual servoing in robotics, computer vision, and augmented reality
CRISAM - Inria Sophia Antipolis - Méditerranée , Inria Rennes – Bretagne Atlantique , IRISA-D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE
Abstract : This paper presents a method and apparatus for building 3D dense visual maps of large scale environments for real-time localisation and autonomous navigation. We propose a spherical ego-centric representation of the environment which is able to reproduce photo-realistic omnidirectional views of captured environments. This representation is composed of a graph of locally accurate augmented spherical panoramas that allows to generate varying viewpoints through novel view synthesis. The spheres are related by a graph of 6 d.o.f. poses which are estimated through multi-view spherical registration. It is shown that this representation can be used to accurately localise a vehicle navigating within the spherical graph, using only a monocular camera for accurate localisation. To perform this task, an efficient direct image registration technique is employed. This approach directly exploits the advantages of the spherical representation by minimising a photometric error between a current image and a reference sphere. Autonomous navigation results are shown in challenging urban environ- ments, containing pedestrians and other vehicles.
Document type :
Conference papers
Intelligent Vehicle (IV'12) Workshop on Navigation, Perception, Accurate Positioning and Mapping for Intelligent Vehicles, Jun 2012, Alcala de Henares, Spain. 2012


https://hal.inria.fr/hal-00752897
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Submitted on : Friday, November 16, 2012 - 3:57:33 PM
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Maxime Meilland, Patrick Rives, Andrew Comport. Dense RGB-D mapping of large scale environments for real-time localisation and autonomous navigation. Intelligent Vehicle (IV'12) Workshop on Navigation, Perception, Accurate Positioning and Mapping for Intelligent Vehicles, Jun 2012, Alcala de Henares, Spain. 2012. <hal-00752897>

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