Tree fruit growers worldwide are grappling with labor shortages in crucial operations such as harvesting and pruning. The development of robotic solutions for these labor-intensive tasks has generated significant interest. However, existing efforts have proven to be excessively expensive, slow, or necessitate orchard reconfiguration for functionality.

In this presentation, I introduce three alternative approaches to agriculture robot development: 1) Introducing a novel soft-growing multi-robot platform to reduce costs and enhance overall responsiveness. 2) Utilizing a cyber-physical system that facilitates human participation for collaborative robotic apple harvesting. 3) Learning human-robot collaboration behaviors to optimize efficiency. Leveraging human-robot interaction to address existing individual shortcomings of humans and robots will enable mutual learning of behaviors to enhance overall efficiency.

The Cornell Institute for Digital Agriculture (CIDA), a faculty led initiative focused on creating a strong voice in the emerging area of Digital Agriculture (DA), invites Dr. Ming Luo to present his research for CIDA’s monthly seminar series.