2026 ASEE Annual Conference & Exposition

Integrating Robotics, Computer Vision, and AI for Automated Stand Count and Vigor Assessment in Cornfields

Presented at Instrumentation in Engineering Education for Field Environments

Manual methods for assessing stand count and plant vigor in large-scale cornfields are labor-intensive, time-consuming, and prone to human error. This work presents an integrated robotic and artificial intelligence (AI) framework that automates plant detection, counting, and health assessment with high accuracy and scalability. An AgileX Scout Mini platform, equipped with an Intel RealSense D435i camera, was used to capture video segments at systematic intervals representing 1/1000th of an acre. The image data were processed using OpenCV and YOLOv8 algorithms to detect and track individual plants across frames, effectively handling challenges such as variable lighting, occlusion, and growth-stage differences. Plant vigor was evaluated through a scoring system based on morphological features, stem robustness, and color-based health indices. The developed method achieved up to 96.67% accuracy in stand count estimation when validated against known seed application rates. The results demonstrate the potential of this approach for practical agricultural applications including crop emergence monitoring, early stress and disease detection, growth rate analysis, and yield forecasting. Future work will focus on using drone imagery to enhance detection accuracy, enable multi-class classification, and extend analytical capabilities for weed and pest identification, disease mapping, and cloud-based data processing. Efforts will also be devoted to design and develop a low-cost user friendly autonomous platform that can be readily utilized in agricultural fields in small farms.

Authors

Mr. Suseel Kumar Yerramsetti University of Maryland Eastern Shore [biography]

Suseel Kumar Yerramsetti is currently a Ph.D. student in the Department of Food and Agricultural Sciences at the University of Maryland Eastern Shore (UMES). Mr. Yerramsetti received his bachelor’s degree in Bioinformatics from Bharath University, Chennai, India, in 2011, and earned his master’s degree in Computer Science from UMES in 2016. He brings an interdisciplinary background that bridges computing, engineering, and agricultural research. His doctoral research focuses on the application of artificial intelligence, robotics, remote sensing, and machine learning for precision agriculture. His work explores integrated, data-driven approaches to support crop monitoring, plant health assessment, yield prediction, and decision-support systems for sustainable crop management. In parallel with his academic research, Mr. Yerramsetti has more than ten years of professional experience in software engineering, application modernization, multi-cloud infrastructure, security governance, data engineering, Internet of Things (IoT) integrations, AI-driven analytics, and machine learning models. He currently works at IBM as a Solution Architect. He previously worked with The Walt Disney Company as a Senior Software Engineer and Cloud Engineer, and with Samsung as a Software Engineer. His broader interests lie at the intersection of artificial intelligence, cloud-based intelligent systems, predictive modeling, and agricultural production, with a focus on translating remote sensing, robotics, and machine learning advances into practical, accessible tools for farmers.
Dr. Abhijit Nagchaudhuri University of Maryland Eastern Shore [biography]

Dr. Abhijit Nagchaudhuri is currently a tenured professor in the Department of Engineering and Aviation Sciences at the University of Maryland Eastern Shore(UMES). Dr. Nagchaudhuri received his baccalaureate degree from Jadavpur University (India) with honors in mechanical engineering in 1983. Thereafter, he worked in a multinational industry for a little over three years before joining Tulane University as a graduate student in the fall of 1987. He received a master’s degree from Tulane University in 1989 and a doctoral degree from Duke University in 1992. He is a member of the American Society for Mechanical Engineers (ASME), the American Society for Engineering Education (ASEE), and, has also been involved with the American Society for Agricultural and Biological Engineers (ASABE). He is actively involved in teaching and research in the fields of (i) robotics and mechatronics, (ii) remote sensing and precision agriculture, and,(iii) biofuels and renewable energy. He has been involved with several extramurally funded projects as PI or Co-PI to support outreach, education, and research activities from various state, federal, and private agencies; served in leadership roles in professional societies; and has received several awards and certificates from his home institution as well as professional societies. He has published more than 90 refereed articles in journals, book chapters, and conference proceedings. He has been involved with several divisions of ASEE including the Minorities in Engineering Division (MIND), and served as the division chair of the Energy Conversion, Conservation, and Nuclear Engineering Division (ECCNED) in 2016. He is a member of the technical committee of IEEE/ASME Mechatronics and Embedded Systems Application(MESA) and has served as the division chair in 2022. He serves as a program committee member of the Maryland Space Grant Consortium.
Mr. Lance Ward University of Maryland Eastern Shore [biography]

I am an undergraduate student researcher at the University of Maryland Eastern Shore currently working on a bachelor's degree in engineering with a concentration in computer engineering.
Ms. Divya vani Singamsetti University of Maryland Eastern Shore [biography]

Divya vani Singamsetti is a Ph.D. student in the Department of Food and Agricultural Sciences at the University of Maryland Eastern Shore (UMES). She holds a Master’s degree in Computer Science (2016) and a Bachelor’s degree in Computer Science Engineering (2014) from Jawaharlal Nehru Technological University, Hyderabad (JNTUH), India. She has over five years of professional experience in software engineering, including application development and testing. Her research interests focus on artificial intelligence and robotics for agricultural applications. Her work centers on robotic crop monitoring and autonomous field navigation, supported by data-driven system design.
Mr. Jesu Raj Pandya University of Maryland Eastern Shore [biography]

Currently a doctoral student in Food & Agriculture Sciences, University of Maryland Eastern Shore (UMES),
MSc - Applied Computer Sciences at UMES,
BSc - Electrical and Electronical Engineering ( JNTU).

Interest in robotics and automation in food prod

Note

The full paper will be available to logged in and registered conference attendees once the conference starts on June 21, 2026, and to all visitors after the conference ends on June 24, 2026

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