3D Mapping of Outdoor Environment Using Clustering Techniques

Manuel Yguel (1, 2) , Olivier Aycard (1, 3)

1 E-MOTION - Geometry and Probability for Motion and Action
2 TH - University of Karlsruhe
3 AMA - Analyse de données, Modélisation et Apprentissage automatique [Grenoble]

The goal of mapping is to build a map of the environment using raw data provided by some sensors embedded on an intelligent vehicle. This map is used by an intelligent vehicle to have knowledge about its surrounding environment to better plan its future actions. In this paper, we present a method, based on occupancy grids [3], to map 3D environment. In this method, we discretize the environment in cells and the shape of each cell is approximated by one or several gaussians in order to achieve a balance between representational complexity and accuracy. Experimental results on 3D real outdoor data provided by a lidar are shown: a map of an urban environment is presented. Moreover a quantitative comparison of our method with state of the art methods is presented to show the interest of the method.

Mots clés: Data Modeling; Learning; Perception; Sensor Data Processing

Domaines: Apprentissage [cs.LG]; Intelligence artificielle [cs.AI]; Robotique [cs.RO]

Manuel Yguel, Olivier Aycard. 3D Mapping of Outdoor Environment Using Clustering Techniques. ICTAI 2011 - 23rd IEEE International Conference on Tools with Artificial Intelligence, Nov 2011, Boca Raton, Florida, United States. pp.403-408, ⟨10.1109/ICTAI.2011.66⟩. ⟨hal-00742597⟩