Biological Systems Engineering

 

First Advisor

Santosh Pitla

Date of this Version

12-2019

Citation

Murman, Joshua N. (2019). Flex-Ro: A Robotic High Throughput Field Phenotyping System (Master's thesis). University of Nebraska-Lincoln, Lincoln, NE

Comments

A Thesis Presented to the Faculty of the Graduate College at the University of Nebraska In Partial Fulfillment of Requirements for the Degree of Master of Science, Major: Agricultural and Biological Systems Engineering, Under the Supervision of Professor Santosh K. Pitla. Lincoln, Nebraska December, 2019.

Copyright (c) 2019 Joshua Murman

Abstract

Research in agriculture is critical to developing techniques to meet the world’s demand for food, fuel, fiber, and feed. Optimization of crop production per unit of land requires scientists across disciplines to collaborate and investigate new areas of science and tools for data collection. The use of robotics has been adopted in several industries to supplement labor, and accurately perform repetitious tasks. However, the use of autonomous robots in commercial agricultural production is still limited. The Flex-Ro (Flexible structured Robotic platform) was developed for use in large area fields as a multipurpose tool to perform monotonous agricultural tasks.

This work presents the design and implementation of the control system for the Flex-Ro machine. The machine control architecture was developed for safe operation with redundant emergency stops and checks. Operators use the remote-control device to maneuver the machine in uncontrolled environments. Autonomous field coverage was developed using global positioning system (GPS) guidance. The guidance system tracked within 4 cm of the guidance line 95% of the time at a travel speed of 4 kph. Waypoint guidance was implemented and demonstrated such that Flex-Ro could be programmed to follow complex paths and curves.

High-throughput plant phenotyping is a continuously developing and evolving field of plant science. The methods used to collect phenotyping data include drones, satellites, manual measurement, and ground rovers. A suite of phenotyping sensors was installed onto the Flex-Ro to cover large field areas. The system was verified in soybean research plots at the University of Nebraska-Lincoln (UNL) Spidercam phenotyping facility. Positive correlations between the Spidercam and Flex-Ro phenotyping data were established. The Flex-Ro was able to statistically distinguish between soybean variety emergence and maturity differences. The late season phenotyping data showed statistical differences between the fully irrigated versus deficit plots. Basic economic calculations estimated the cost to operate the Flex-Ro machine for field phenotyping use at approximately $5.50/ha.

Advisor: Santosh K. Pitla

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