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Conference Paper

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

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

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

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

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Citation

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


Cite as: https://hdl.handle.net/11858/00-001M-0000-0013-B5C6-2
Abstract
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.