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Sensors 2017, 17(1), 214; doi:10.3390/s17010214

Vinobot and Vinoculer: Two Robotic Platforms for High-Throughput Field Phenotyping

1
ViGIR Lab, Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO 65211, USA
2
Division of Plant Sciences, University of Missouri, Columbia, MO 65211, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Gabriel Oliver-Codina, Nuno Gracias and Antonio M. López
Received: 24 October 2016 / Revised: 26 December 2016 / Accepted: 13 January 2017 / Published: 23 January 2017
(This article belongs to the Special Issue Vision-Based Sensors in Field Robotics)

Abstract

In this paper, a new robotic architecture for plant phenotyping is being introduced. The architecture consists of two robotic platforms: an autonomous ground vehicle (Vinobot) and a mobile observation tower (Vinoculer). The ground vehicle collects data from individual plants, while the observation tower oversees an entire field, identifying specific plants for further inspection by the Vinobot. The advantage of this architecture is threefold: first, it allows the system to inspect large areas of a field at any time, during the day and night, while identifying specific regions affected by biotic and/or abiotic stresses; second, it provides high-throughput plant phenotyping in the field by either comprehensive or selective acquisition of accurate and detailed data from groups or individual plants; and third, it eliminates the need for expensive and cumbersome aerial vehicles or similarly expensive and confined field platforms. As the preliminary results from our algorithms for data collection and 3D image processing, as well as the data analysis and comparison with phenotype data collected by hand demonstrate, the proposed architecture is cost effective, reliable, versatile, and extendable. View Full-Text
Keywords: field phenotyping; robotics; vision; 3D reconstruction; mobile robotics field phenotyping; robotics; vision; 3D reconstruction; mobile robotics
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Shafiekhani, A.; Kadam, S.; Fritschi, F.B.; DeSouza, G.N. Vinobot and Vinoculer: Two Robotic Platforms for High-Throughput Field Phenotyping. Sensors 2017, 17, 214.

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