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Proceedings Paper

Coordination and control for automatic mobile ground control points in agricultural remote sensing
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Paper Abstract

Ground control points (GCPs) are critical for agricultural applications that require geographic registration, radiometric and height calibrations of images when overlaying images collected at different times. However, in terms of using conventional GCPs, it is time-consuming and labor-intensive to measure, distribute and collect all GCPs around a large field. An automatic mobile GCP is essential to replace the conventional GCPs, which can collaborate with the UAV during the flight allowing the mobile GCP to be captured in the images based on a proposed cooperation strategy. To investigate the plant phenotyping across a field based on multi-types of imaging sensors (RGB, multispectral, and thermal), two radiometric calibration references and two temperature calibration references were installed on the top of the mobile GCP. The mobile GCP used for auto-guidance driving is a four-wheel platform with differential speed steering control for front-wheel, which equipped with two RTK-GPS units for position determination, a navigation computer for path planning and tracking, an integrated driving controller for steering and traveling. The traveling angles and velocities of the wheels at each location can be generated using a path-tracking algorithm to follow a predefined driving map based on UAV’s flight planning. It is noteworthy that all positions of the mobile GCP can be recorded on the UAV during the flight for future image mosaicking. The automatic mobile GCP enables to reliably recognize and predict the behavior and activities of the UAVs in agricultural remote sensing and has a potential to improve the efficiency of the data collection in the field.

Paper Details

Date Published: 14 May 2019
PDF: 6 pages
Proc. SPIE 11008, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping IV, 110080B (14 May 2019); doi: 10.1117/12.2518260
Show Author Affiliations
Xiongzhe Han, Texas A&M Univ. (United States)
J. Alex Thomasson, Texas A&M Univ. (United States)


Published in SPIE Proceedings Vol. 11008:
Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping IV
J. Alex Thomasson; Mac McKee; Robert J. Moorhead, Editor(s)

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