The Robotanist: A ground-based agricultural robot for high-throughput crop phenotyping
Conference Paper, Proceedings of (ICRA) International Conference on Robotics and Automation, pp. 3634 - 3639, May, 2017
Abstract
The established processes for measuring physiological and morphological traits (phenotypes) of crops in outdoor test plots are labor intensive and error-prone. Low-cost, reliable, field-based robotic phenotyping will enable geneticists to more easily map genotypes to phenotypes, which in turn will improve crop yields. In this paper, we present a novel robotic ground-based platform capable of autonomously navigating below the canopy of row crops such as sorghum or corn. The robot is also capable of deploying a manipulator to measure plant stalk strength and gathering phenotypic data with a modular array of non-contact sensors. We present data obtained from deployments to Sorghum bicolor test plots at various sites in South Carolina, USA.
BibTeX
@conference{Mueller-Sim-2017-105841,author = {Tim Mueller-Sim and Merritt Jenkins and Justin Abel and George Kantor},
title = {The Robotanist: A ground-based agricultural robot for high-throughput crop phenotyping},
booktitle = {Proceedings of (ICRA) International Conference on Robotics and Automation},
year = {2017},
month = {May},
pages = {3634 - 3639},
keywords = {agricultural robotics, manipulation, computer vision, field-based robotic phenotyping, high-throughput crop phenotyping, ground-based agricultural robot},
}
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