3D Point Clouds Segmentation for Autonomous Ground Vehicle

  • Danilo Habermann USP
  • Alberto Hata USP
  • Denis Wolf USP
  • Fernando S. Osório USP

Resumo


Point clouds segmentation is an essential step to improve the performance of obstacle detection and classification in areas of autonomous ground vehicles and mobile robotics. This paper presents a study and comparison of the performance of segmentation methods using point clouds coming from a 3D laser sensor, more specifically obtained from a Velodyne HDL32.
Palavras-chave: Three-dimensional displays, Image segmentation, Robot sensing systems, Lasers, Land vehicles, Laser radar, point clouds segmentation, 3D Lidar, autonomous ground vehicle
Publicado
04/11/2013
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HABERMANN, Danilo; HATA, Alberto; WOLF, Denis; OSÓRIO, Fernando S.. 3D Point Clouds Segmentation for Autonomous Ground Vehicle. In: SIMPÓSIO BRASILEIRO DE ENGENHARIA DE SISTEMAS COMPUTACIONAIS (SBESC), 3. , 2013, Niterói/RJ. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2013 . p. 143-148. ISSN 2237-5430.