Real Time Vision System for Obstacle Detection and Localization on FPGAReport as inadecuate

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1 LAAS-RAP - Équipe Robotique, Action et Perception LAAS - Laboratoire d-analyse et d-architecture des systèmes Toulouse

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 : Obstacle detection indoor robotics inverse perspective mapping FPGA - field-programmable gate array

Author: Ali Alhamwi - Bertrand Vandeportaele - Jonathan Piat -



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