Abstract
AbstractSeveral recent works deal with 3D data in mobile robotic problems: mapping and SLAM related problems. Data come from any kind of sensor (time of flight cameras and 3D lasers) providing a huge amount of unorganized 3D data. In this paper we detail an efficient method to build complete 3D models from a Growing Neural Gass (GNG). The GNG obtained is then applied to a sequence. From neurons in the GNG, we propose to calculate planar patches and thus obtaining a fast method to compute the movement performed by a mobile robot by means of a 3D models registration algorithm.KeywordsGNGegomotionregistrationplanar patches
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