A Spherical Robot-Centered Representation for Urban Navigation

Maxime Meilland 1 Andrew I. Comport 2 Patrick Rives 3
1 AROBAS - Advanced Robotics and Autonomous Systems
CRISAM - Inria Sophia Antipolis - Méditerranée
3 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 describes a generic method for vision-based navigation in real urban environments. The proposed approach relies on a representation of the scene based on spherical images augmented with depth information and a spherical saliency map, both constructed in a learning phase. Saliency maps are built by analyzing useful information of points which best condition spherical projections constraints in the image. During navigation, an image-based registration technique combined with robust outlier rejection is used to precisely locate the vehicle. The main objective of this work is to improve computational time by better representing and selecting information from the reference sphere and current image without degrading matching. It will be shown that by using this pre-learned global spherical memory no error is accumulated along the trajectory and the vehicle can be precisely located without drift.
Type de document :
Communication dans un congrès
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Oct 2010, Taipei, Taiwan. 2010, <10.1109/IROS.2010.5650380>
Liste complète des métadonnées

https://hal.archives-ouvertes.fr/hal-01357378
Contributeur : Andrew Comport <>
Soumis le : lundi 29 août 2016 - 16:35:38
Dernière modification le : jeudi 9 février 2017 - 16:03:01

Identifiants

Citation

Maxime Meilland, Andrew I. Comport, Patrick Rives. A Spherical Robot-Centered Representation for Urban Navigation. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Oct 2010, Taipei, Taiwan. 2010, <10.1109/IROS.2010.5650380>. <hal-01357378>

Partager

Métriques

Consultations de la notice

327