Authors:
Dries Hulens
;
Maarten Vandersteegen
and
Toon Goedemé
Affiliation:
KU Leuven, Belgium
Keyword(s):
Unmanned Aerial Vehicle, Agriculture, Orchard, Vision-based Navigation.
Related
Ontology
Subjects/Areas/Topics:
Color and Texture Analyses
;
Computer Vision, Visualization and Computer Graphics
;
Features Extraction
;
Image and Video Analysis
;
Segmentation and Grouping
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.
(More)