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UAV Localization in Row Crops
Author(s) -
Anthony David,
Detweiler Carrick
Publication year - 2017
Publication title -
journal of field robotics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.152
H-Index - 96
eISSN - 1556-4967
pISSN - 1556-4959
DOI - 10.1002/rob.21706
Subject(s) - inertial measurement unit , position (finance) , laser scanning , computer science , field (mathematics) , scanner , process (computing) , orientation (vector space) , precision agriculture , remote sensing , lidar , artificial intelligence , real time computing , computer vision , simulation , laser , geography , agriculture , physics , geometry , mathematics , archaeology , finance , pure mathematics , optics , economics , operating system
High‐flying unmanned aerial vehicles (UAVs) are transforming industrial and research agriculture by delivering high spatiotemporal resolution data on a field environment. While current UAVs fly high above fields collecting aerial imagery, future low‐flying aircraft will directly interact with the environment and will utilize a wider variety of sensors. Safely and reliably operating close to unstructured environments requires improving UAVs' sensing, localization, and control algorithms. To this end, we investigate localizing a micro‐UAV in corn phenotyping trials using a laser scanner and IMU to control the altitude and position of the vehicle relative to the plant rows. In this process, the laser scanner is not only a means of localization, but also a scientific instrument for measuring plant properties. Experimental evaluations demonstrate that the is capable of safely and reliably operating in real‐world phenotyping trials. We experimentally validate the system in both low and high wind conditions in fully mature corn fields. Using test data from 18 test flights, we show that the UAV is capable of localizing its position to within one field row of the true position.