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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)

Abstract

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.

Keywords

Optical Flow Ground Plane Camera Frame Obstacle Detection World Frame 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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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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