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Author (up) Andrew Nolan; Daniel Serrano; Aura Hernandez-Sabate; Daniel Ponsa; Antonio Lopez
Title Obstacle mapping module for quadrotors on outdoor Search and Rescue operations Type Conference Article
Year 2013 Publication International Micro Air Vehicle Conference and Flight Competition Abbreviated Journal
Volume Issue Pages
Keywords UAV
Abstract Obstacle avoidance remains a challenging task for Micro Aerial Vehicles (MAV), due to their limited payload capacity to carry advanced sensors. Unlike larger vehicles, MAV can only carry light weight sensors, for instance a camera, which is our main assumption in this work. We explore passive monocular depth estimation and propose a novel method Position Aided Depth Estimation
(PADE). We analyse PADE performance and compare it against the extensively used Time To Collision (TTC). We evaluate the accuracy, robustness to noise and speed of three Optical Flow (OF) techniques, combined with both depth estimation methods. Our results show PADE is more accurate than TTC at depths between 0-12 meters and is less sensitive to noise. Our findings highlight the potential application of PADE for MAV to perform safe autonomous navigation in
unknown and unstructured environments.
Address Toulouse; France; September 2013
Corporate Author Thesis
Publisher Place of Publication Editor
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Area Expedition Conference IMAV
Notes ADAS; 600.054; 600.057;IAM Approved no
Call Number Admin @ si @ NSH2013 Serial 2371
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