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

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.

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 Creators:
Grabe, V1, 2, Author              
Bülthoff, HH1, 2, Author              
Robuffo Giordano, P1, 2, Author              
Affiliations:
1Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497797              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 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.

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 Dates: 2012-10
 Publication Status: Published in print
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 Identifiers: DOI: 10.1109/IROS.2012.6386234
BibTex Citekey: GrabeBR2012
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Title: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2012)
Place of Event: Vilamoura, Portugal
Start-/End Date: 2012-10-07 - 2012-10-12

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Title: 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems
Source Genre: Proceedings
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Publ. Info: Piscataway, NJ, USA : IEEE
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 2153 - 2159 Identifier: ISBN: 978-1-4673-1737-5