Anzeige
Erschienen in:
2015 | OriginalPaper | Buchkapitel
Real Time Vision System for Obstacle Detection and Localization on FPGA
verfasst von : Ali Alhamwi, Bertrand Vandeportaele, Jonathan Piat
Erschienen in: Computer Vision Systems
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
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.