Real Time Vision System for Obstacle Detection and Localization on FPGA

  • Ali AlhamwiEmail author
  • Bertrand Vandeportaele
  • Jonathan Piat
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9163)


Obstacle detection is a mandatory function for a robot navigating in an indoor environment especially when interaction with humans is done in a cluttered environment. Commonly used vision-based solutions like SLAM (Simultaneous Localization and Mapping) or optical flow tend to be computation intensive and require powerful computation resources to meet low speed real-time constraints. Solutions using LIDAR (Light Detection And Ranging) sensors are more robust but not cost effective. This paper presents a real-time hardware architecture for vision-based obstacle detection and localization based on IPM (Inverse Perspective Mapping) for obstacle detection, and Otsu’s method plus Bresenham’s algorithm for obstacle segmentation and localization under the hypothesis of a flat ground. The proposed architecture combines cost effectiveness, high frame-rate with low latency, low power consumption and without any prior knowledge of the scene compared to existing implementations.


Optical Flow Ground Plane Camera Frame Obstacle Detection World Frame 
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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Ali Alhamwi
    • 1
    Email author
  • Bertrand Vandeportaele
    • 1
    • 2
  • Jonathan Piat
    • 1
    • 2
  1. 1.LAAS-CNRSToulouse Cedex 4France
  2. 2.University of ToulouseToulouse Cedex 4France

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