A real-time GPU-based wall detection algorithm for mapping and navigation in indoor environments

  • Authors:

  • Hadi Moradi;Eun Kwon;Dae Neung Sohn;JungHyun Han

  • Affiliations:

  • Department of Computer Science, University of Southern California, LA, CA;College of Information and Communications, Korea University, Seoul, Korea;College of Information and Communications, Korea University, Seoul, Korea;College of Information and Communications, Korea University, Seoul, Korea

  • Venue:
  • Proceedings of the 2007 conference on Human interface: Part II
  • Year:
  • 2007

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Abstract

In robotic applications, there is a growing trend for developing human-like real-time interaction capabilities. A good example can be found in Simultaneous localization and mapping technique, where a robot or an autonomous vehicle builds up a map within an unknown environment while at the same time keeping track of its current position. Especially in indoor environments, wall detection is often a critical part of SLAM: it plays a key role in scene interpretation and 3D workspace modeling. Further, it also reduces the size of the map. This paper presents an effective and real-time approach for detecting walls in indoor environment using GPU (graphics processing unit). The experimental results show the feasibility of using GPU as a coprocessor in robotic applications.