Real-time Vision-based UAV Navigation in Fruit Orchards

Dries Hulens, Maarten Vandersteegen, Toon Goedemé

2017

Abstract

Unmanned Aerial Vehicles (UAV) enable numerous agricultural applications such as terrain mapping, monitor crop growth, detecting areas with diseases and so on. For these applications a UAV flies above the terrain and has a global view of the plants. When the individual fruits or plants have to be examined, an oblique view is better, e.g. via an inspection-camera mounted on expensive all-terrain wheeled robots that drive through the orchard. However, in this paper we aim to autonomously navigate through the orchard with a low-cost UAV and cheap sensors (e.g. a webcam). Evidently, this is challenging since every orchard or even every corridor looks different. For this we developed a vision-based system that detects the center and end of the corridor to autonomously navigate the UAV towards the end of the orchard without colliding with the trees. Furthermore extensive experiments were performed to prove that our algorithm is able to navigate through the orchard with high accuracy and in real-time, even on embedded hardware. A connection with a ground station is thus unnecessary which makes the UAV fully autonomous.

Paper Citation

in Harvard Style

Hulens D., Vandersteegen M. and Goedemé T. (2017). Real-time Vision-based UAV Navigation in Fruit Orchards . In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2017) ISBN 978-989-758-225-7, pages 617-622. DOI: 10.5220/0006242906170622

in Bibtex Style

@conference{visapp17,
author={Dries Hulens and Maarten Vandersteegen and Toon Goedemé},
title={Real-time Vision-based UAV Navigation in Fruit Orchards},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2017)},
year={2017},
pages={617-622},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006242906170622},
isbn={978-989-758-225-7},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2017)
TI - Real-time Vision-based UAV Navigation in Fruit Orchards
SN - 978-989-758-225-7
AU - Hulens D.
AU - Vandersteegen M.
AU - Goedemé T.
PY - 2017
SP - 617
EP - 622
DO - 10.5220/0006242906170622