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Real-Time On-Board Obstacle Avoidance for UAVs based on Embedded Stereo Vision

Ruf, Boitumelo 1; Monka, Sebastian; Kollmann, Matthias; Grinberg, Michael
1 Institut für Photogrammetrie und Fernerkundung (IPF), Karlsruher Institut für Technologie (KIT)

Abstract (englisch):

In order to improve usability and safety, modern unmanned aerial vehicles (UAVs) are equipped with sensors to monitor the environment, such as laser-scanners and cameras. One important aspect in this monitoring process is to detect obstacles in the flight path in order to avoid collisions. Since a large number of consumer UAVs suffer from tight weight and power constraints, our work focuses on obstacle avoidance based on a lightweight stereo camera setup. We use disparity maps, which are computed from the camera images, to locate obstacles and to automatically steer the UAV around them. For disparity map computation we optimize the well-known semi-global matching (SGM) approach for the deployment on an embedded FPGA. The disparity maps are then converted into simpler representations, the so called U-/V-Maps, which are used for obstacle detection. Obstacle avoidance is based on a reactive approach which finds the shortest path around the obstacles as soon as they have a critical distance to the UAV. One of the fundamental goals of our work was the reduction of development costs by closing the gap between application development and hardware optimization. ... mehr

Verlagsausgabe §
DOI: 10.5445/IR/1000086556
Veröffentlicht am 12.11.2018
DOI: 10.5194/isprs-archives-XLII-1-363-2018
Zitationen: 7
Zitationen: 11
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Photogrammetrie und Fernerkundung (IPF)
KIT-Zentrum Klima und Umwelt (ZKU)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2018
Sprache Englisch
Identifikator ISSN: 1682-1750
KITopen-ID: 1000086556
Erschienen in The international archives of photogrammetry, remote sensing and spatial information sciences
Verlag Copernicus Publications
Band XLII-1
Seiten 363–370
Nachgewiesen in Dimensions
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