Vision-based sense-and-avoid framework for unmanned aerial vehicles

This paper describes a vision-based sense-and-avoid framework to detect approaching aircraft especially observed with cluttered background. The proposed framework consists of a vision system with a camera that processes the incoming images using a series of algorithms in real time to isolate moving...

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Bibliographic Details
Published in:IEEE transactions on aerospace and electronic systems 2015-10, Vol.51 (4), p.3427-3439
Main Authors: Sungsik Huh, Sungwook Cho, Yeondeuk Jung, Shim, David Hyunchul
Format: Article
Language:English
Subjects:
Aerials
Aerospace electronics
Aircraft
Aircraft components
Algorithms
Cameras
Classification
Electronic systems
Feature extraction
Image classification
Object detection
Sensors
Unmanned aerial vehicles
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Summary:This paper describes a vision-based sense-and-avoid framework to detect approaching aircraft especially observed with cluttered background. The proposed framework consists of a vision system with a camera that processes the incoming images using a series of algorithms in real time to isolate moving aerial objects on the image plane and classify them using a particle filter. Once an approaching aerial object has been detected on a potential collision course, the aircraft performs an evasive maneuver. The performance of the proposed sense-and-avoid algorithm is validated in a series of test flights using two unmanned aerial vehicles.
ISSN:0018-9251
1557-9603
DOI:10.1109/TAES.2015.140252