Cyber-Physical Systems in Agriculture: Integrating Robotics and Humans

Tree fruit growers worldwide are facing significant labor shortages in critical operations such as harvesting and pruning. As a result, the development of robotic solutions for these labor-intensive tasks has attracted increasing attention. However, many existing approaches remain too expensive, slow, or require substantial orchard reconfiguration to be effective.

In this presentation, I introduce three alternative approaches to agricultural robot development. First, a cyber-physical system is proposed to enable human participation alongside machine learning for collaborative robotic apple harvesting. Second, a novel soft-growing multi-robot platform is developed to reduce system cost while improving responsiveness. Third, human–robot collaboration behaviors are learned to optimize overall efficiency.

By leveraging human–robot interaction, this work aims to address the limitations of both humans and robots, enabling mutual learning and ultimately improving system performance in real-world agricultural environments.

Dr. Ming Luo is currently a Flaherty Assistant Professor in the School of Mechanical and Materials Engineering at Washington State University and will be promoted to Associate Professor in August. Dr. Luo directs the Mechanically Intelligent Autonomous Robotics Laboratory and is a Senior Member of IEEE. Dr. Luo received his Ph.D. in Robotic Engineering from Worcester Polytechnic Institute in 2017 and completed his postdoctoral training at Stanford University from 2018 to 2020. Dr. Luo’s research interests include agricultural robotics, soft robotics, snake robots, origami-inspired robots, and haptics. His work has been supported by the National Science Foundation (NSF), the United States Department of Agriculture (USDA), the National Institute of Food and Agriculture (NIFA), and the Washington Tree Fruit Research Commission. His research has been featured in outlets such as IEEE Xplore, Reuters, The Verge, and The Wall Street Journal.

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