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Robust Optical-Flow Based Self-Motion Estimation for a Quadrotor UAV

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons83942

Grabe,  V
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons83839

Bülthoff,  HH
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons84174

Robuffo Giordano,  P
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Zitation

Grabe, V., Bülthoff, H., & Robuffo Giordano, P. (2012). Robust Optical-Flow Based Self-Motion Estimation for a Quadrotor UAV. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2012) (pp. 2153-2159). Piscataway, NJ, USA: IEEE.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0013-B5C6-2
Zusammenfassung
Robotic vision has become an important field of research for micro aerial vehicles in the recent years. While many approaches for autonomous visual control of such vehicles rely on powerful ground stations, the increasing availability of small and light hardware allows for the design of more independent systems. In this context, we present a robust algorithm able to recover the UAV ego-motion using a monocular camera and on-board hardware. Our method exploits the continuous homography constraint so as to discriminate among the observed feature points in order to classify those belonging to the dominant plane in the scene. Extensive experiments on a real quadrotor UAV demonstrate that the estimation of the scaled linear velocity in a cluttered environment improved by a factor of 25 compared to previous approaches.