Bionote
Kendall Koe is a PhD Candidate in the Siebel School of Computing and Data Science at the University of Illinois Urbana-Champaign, advised by Dr. Girish Chowdhary in the Distributed Autonomous Systems Laboratory (DASLAB). He collaborates with researchers in the Monolithic Systems Lab and at Iowa State University as part of the COALESCE (COntext-Aware LEarning for Sustainable CybEr-agricultural) program. His research focuses on developing practical robotic systems to support and enhance human capabilities. He is also passionate about teaching Computer Science and Robotics at all levels, having worked with students from junior high through graduate studies.
Presentation Abstract
Due to labor shortages in specialty crop industries, a need for robotic automation to increase agricultural efficiency and productivity has arisen. Previous manipulation systems harvest well in uncluttered and structured environments. High tunnel environments are more compact and cluttered in nature, requiring a rethinking of the large form factor systems and grippers. We propose a novel co-designed framework incorporating a global detection camera and a local eye-in-hand camera that demonstrates precise localization of small fruits via closed-loop visual feedback and reliable error handling. Field experiments in high tunnels show that our system can reach 85.0% of cherry tomato fruit in 10.98s on average.
Co-authors: Poojan Kalpeshbhai Shah, Benjamin Walt, Jordan Westphal, Samhita Marri, Shivani Kamtikar, James Seungbum Nam, Naveen Kumar Uppalapati, Girish Krishnan, Girish Chowdhary