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AMAR – Autonomous Modular Agricultural Robot

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Conference

2022 ASEE Gulf Southwest Annual Conference

Location

Prairie View, Texas

Publication Date

March 16, 2022

Start Date

March 16, 2022

End Date

March 18, 2022

Tagged Topic

Diversity

Page Count

6

DOI

10.18260/1-2--39158

Permanent URL

https://peer.asee.org/39158

Download Count

446

Paper Authors

biography

Ana Elisa P. Goulart Texas A&M University

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Ana Elisa Goulart received a bachelor’s degree in electrical engineering from the Federal School of Engineering of Itajuba (EFEI), in Brazil. While working in the industry, she received a M. Sc. degree in Information Systems Management from the Pontificial Catholic University of Campinas, in 1997. She moved to the United States in 1997 where she earned a M. Sc. in Computer Engineering at North Carolina State University, Raleigh, NC; followed by a Ph.D. in Electrical and Computer Engineering at Georgia Tech, Atlanta, GA, in 2005. She is currently an Associate Professor in the Electronics Systems Engineering Technology program at Texas A&M University, in College Station, TX. Her research interests include protocols for real-time voice and video communications and their performance, IP-based emergency communications, last-mile communication links for the SmartGrid, rural telecommunications, and behavior-driven development.

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Mondray Matus AutoAg

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MaKayla Griffith

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Abstract

Weed removal is a task that can benefit from farm automation. However, most automation products are too expensive and are designed for large farms. To address this problem of weed removal for small organic farms and aging farmers, this paper presents the design of the Autonomous Modular Agricultural Robot (AMAR), which is a prototype of a solar-powered farming robot that uses machine learning (ML) algorithms to identify and remove weeds. Initial experiments show that AMAR performs binary classification to decide whether to destroy undesired plants (weeds) or preserve desired plants (crops of peppers). When a weed is detected, a robotic arm cuts the leaves of the weed. AMAR also has the ability to inspect crops without the need for fences or boundary devices, communicates with a user interface that can do several things: track the robot’s location, stop it in an emergency, show weather information, and collect data for analysis and improvements to the system.

Goulart, A. E. P., & Matus, M., & Griffith, M. (2022, March), AMAR – Autonomous Modular Agricultural Robot Paper presented at 2022 ASEE Gulf Southwest Annual Conference, Prairie View, Texas. 10.18260/1-2--39158

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