A dense map building approach from spherical RGBD images

Tawsif Gokhool (1) , Maxime Meilland (2) , Patrick Rives (1) , Eduardo Fernandez-Moral (3)

1 Lagadic - Visual servoing in robotics, computer vision, and augmented reality
2 Laboratoire d'Informatique, Signaux, et Systèmes de Sophia-Antipolis (I3S) / Equipe SYSTEMES
3 ETS - Escuela Técnica Superior de Ingeniería Informática

Visual mapping is a required capability for practical autonomous mobile robots where there exists a grow- ing industry with applications ranging from the service to industrial sectors. Prior to map building, Visual Odometry(VO) is an essential step required in the process of pose graph construction. In this work, we first propose to tackle the pose estimation problem by using both photometric and geometric information in a direct RGBD image registration method. Secondly, the mapping problem is tackled with a pose graph representation, whereby, given a database of augmented visual spheres, a travelled trajectory with redundant information is pruned out to a skeletal pose graph. Both methods are evaluated with data acquired with a recently proposed omnidirectional RGBD sensor for indoor environments.

Domaines: Robotique [cs.RO]; Informatique [cs]

Tawsif Gokhool, Maxime Meilland, Patrick Rives, Eduardo Fernandez-Moral. A dense map building approach from spherical RGBD images. Int. Conf. on Computer Vision Theory and Applications, VISAPP, Jan 2014, Lisbon, Portugal. ⟨hal-01086902⟩