Autonomous UAVs wildlife detection using thermal imaging, predictive navigation and computer vision

Ward, Sean, Hensler, Jordon, Alsalam, Bilal, & Gonzalez, Luis Felipe (2016) Autonomous UAVs wildlife detection using thermal imaging, predictive navigation and computer vision. In Proceedings of the 2016 IEEE Aerospace Conference, IEEE, Yellowstone Conference Center, Big Sky, Montana, pp. 1-8.

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There is an increased interest on the use of Unmanned Aerial Vehicles (UAVs) for wildlife and feral animal monitoring around the world. This paper describes a novel system which uses a predictive dynamic application that places the UAV ahead of a user, with a low cost thermal camera, a small onboard computer that identifies heat signatures of a target animal from a predetermined altitude and transmits that target’s GPS coordinates. A map is generated and various data sets and graphs are displayed using a GUI designed for easy use. The paper describes the hardware and software architecture and the probabilistic model for downward facing camera for the detection of an animal. Behavioral dynamics of target movement for the design of a Kalman filter and Markov model based prediction algorithm are used to place the UAV ahead of the user. Geometrical concepts and Haversine formula are applied to the maximum likelihood case in order to make a prediction regarding a future state of the user, thus delivering a new way point for autonomous navigation. Results show that the system is capable of autonomously locating animals from a predetermined height and generate a map showing the location of the animals ahead of the user.

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ID Code: 92309
Item Type: Conference Paper
Refereed: Yes
Additional URLs:
Keywords: Thermal Imaging, UAV, Predictive Navigation, Computer Vision, Wildlife Detection, FLIR
DOI: 10.1109/AERO.2016.7500671
ISBN: 978-1-4673-7677-8
Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > AEROSPACE ENGINEERING (090100) > Aircraft Performance and Flight Control Systems (090104)
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600) > Control Systems Robotics and Automation (090602)
Divisions: Current > Research Centres > Australian Research Centre for Aerospace Automation
Current > Institutes > Institute for Future Environments
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2016 IEEE
Copyright Statement: Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Deposited On: 27 Jan 2016 01:59
Last Modified: 21 Jun 2017 16:23

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