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Open AccessArticle

Robotic Detection and Grasp of Maize and Sorghum: Stem Measurement with Contact

1
Department of Biological Systems Engineering, University of Nebraska-Lincoln, Lincoln, NE 68583, USA
2
Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE 68583, USA
*
Author to whom correspondence should be addressed.
Robotics 2020, 9(3), 58; https://doi.org/10.3390/robotics9030058
Received: 28 May 2020 / Revised: 22 July 2020 / Accepted: 24 July 2020 / Published: 28 July 2020
(This article belongs to the Section Agricultural and Field Robotics)
Frequent measurements of the plant phenotypes make it possible to monitor plant status during the growing season. Stem diameter is an important proxy for overall plant biomass and health. However, the manual measurement of stem diameter in plants is time consuming, error prone, and laborious. The use of agricultural robots to automatically collect plant phenotypic data for trait measurements can overcome many of the drawbacks of manual phenotyping. The objective of this research was to develop a robotic system that can automatically detect and grasp the stem, and measure its diameter of maize and sorghum plants. The robotic system comprises of a four degree of freedom robotic manipulator, a time-of-flight camera for vision system, and a linear potentiometer sensor to measure the stem diameter. Deep learning and conventional image processing were used to detect stem in images and find grasping point of stem, respectively. An experiment was conducted in a greenhouse using maize and sorghum plants to evaluate the performance of the robotic system. The system demonstrated successful grasping of stem and a high correlation between manual and robotic measurements of diameter depicting its ability to be used as a prototype to integrate other sensors to measure different physiological and chemical attributes of the stem. View Full-Text
Keywords: agricultural robotics; deep learning; Faster R-CNN; image processing; plant phenotyping; stem diameter agricultural robotics; deep learning; Faster R-CNN; image processing; plant phenotyping; stem diameter
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MDPI and ACS Style

Atefi, A.; Ge, Y.; Pitla, S.; Schnable, J. Robotic Detection and Grasp of Maize and Sorghum: Stem Measurement with Contact. Robotics 2020, 9, 58.

AMA Style

Atefi A, Ge Y, Pitla S, Schnable J. Robotic Detection and Grasp of Maize and Sorghum: Stem Measurement with Contact. Robotics. 2020; 9(3):58.

Chicago/Turabian Style

Atefi, Abbas; Ge, Yufeng; Pitla, Santosh; Schnable, James. 2020. "Robotic Detection and Grasp of Maize and Sorghum: Stem Measurement with Contact" Robotics 9, no. 3: 58.

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