DocumentCode :
2390258
Title :
Inertial aided SIFT for time to collision estimation
Author :
Cohen, Benjamin ; Byrne, Jeffrey
Author_Institution :
GRASP Lab, University of Pennsylvania, USA
fYear :
2009
fDate :
12-17 May 2009
Firstpage :
1613
Lastpage :
1614
Abstract :
Visual time to collision estimation for small or micro air vehicles is challenging due to aggressive 6-DOF motion, real time performance requirements and significant size, weight and power constraints of the platform. Recent work in collision detection using insect inspired optical flow based methods have been demonstrated in low power hardware implementations [1][2][3][4], but have not achieved the obstacle detection and false alarm rate performance necessary for practical deployment. This performance is sensitive to correspondence errors in the optical flow field, so one approach to improving performance is to use a richer feature set for correspondence, along with calibrated inertial information from the platform to aid correspondence. In this video, we show proof of concept results for such an approach. Estimation results are noisy, but encouraging, and given that SIFT feature correspondence has been demonstrated in real time on low power GPUs, it has the potential for future small UAV integration.
Keywords :
Cameras; Feature extraction; Focusing; Geometry; Inertial navigation; Motion estimation; Optical sensors; Remotely operated vehicles; Unmanned aerial vehicles; Vehicle safety;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Automation, 2009. ICRA '09. IEEE International Conference on
Conference_Location :
Kobe
ISSN :
1050-4729
Print_ISBN :
978-1-4244-2788-8
Electronic_ISBN :
1050-4729
Type :
conf
DOI :
10.1109/ROBOT.2009.5152886
Filename :
5152886
Link To Document :
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