USWBSI Abstract Viewer

2021 National Fusarium Head Blight Forum


FHB Management (MGMT)

Poster # 102

Development of a Lightweight Quadruped for Real-Time FHB Phenotyping Under Variable Field Conditions

Authors & Affiliations:

David Aviles1, Ce Yang2, An Min2, Cory Hirsch3, Brian J. Steffenson3
1. University of Minnesota - Duluth, Department of Mechanical Engineering, Duluth, MN 2. University of Minnesota - Twin Cities, Department of Bioproducts and Biosystems Engineering, Saint Paul, MN 3. University of Minnesota, Department of Plant Pathology, Saint Paul, MN

Corresponding Author:

Ce Yang
University of Minnesota - Twin Cities
ceyang@umn.edu

Abstract:

In Fusarium Head Blight (FHB) disease nurseries, overhead irrigation is typically used to maintain sufficient moisture on the spikes of wheat and barley plants to achieve optimal infection levels. However, these irrigation treatments can often lead to excessively wet and muddy field conditions, which may hinder the performance of many ground-based, high-throughput phenotyping platforms. A lightweight quadruped with walking capability was developed to handle phenotyping tasks under variable field conditions. The flexible quadruped prototype is controlled by a Raspberry Pi 4 microcontroller and contains 12 servo motors to achieve the needed degrees of freedom on the legs of the robotic dog. One more servo motor is used to control a Pi camera to capture images while traveling in the trial plots. The frame of the quadruped prototype was designed and printed by a 3D printer with durable polylactic acid plastic materials with 80% filling, and the shell of the quadruped was 3D printed with the same material with 100% filling. The size of the quadruped is 14-in in width, 21-in in length and 12-in tall when standing, which will accommodate with the spacing and plant height in the FHB disease nurseries and breeding plots. We have developed robust disease detection algorithms that work with images obtained from different distances and angles as illuminated by natural sunlight. By integrating the quadruped platform with improved lightweight edge-computing models that are currently under development in the AgRobotics Laboratory, we expect to achieve real-time FHB phenotyping under any type of weather and field conditions.


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