Robotics in high tunnel agriculture: perception-driven harvesting and crop monitoring in unstructured environments

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. The system is evaluated in both lab and high tunnel environments for berry harvesting. Second, we extend this framework to DetectCluster2Cut for peduncle-based cluster harvesting of cherry tomatoes, introducing monocular-based depth filtering and peduncle angle estimation. Finally, we propose Nav2Inspect—a navigation and inspection pipeline that integrates CropFollow++ row-following, cluster detection, multi-view close-up imaging, and a fruit-surface pest detection model including pest damages from stink bugs, stilt bugs, and caterpillars. Together, these systems lay a foundation for modular closed-loop perception and manipulation pipelines, offering scalable solutions for real-time in-field harvesting and inspection.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Mechanical Engineering

Grantor

University of Illinois Urbana-Champaign

Year dc:date

2025

Author dc:creator

• Shah, Poojan Kalpeshbhai

Contributors dc:contributor

• Krishnan, Girish

• Agricultural Robotics
• Robotic Harvesting
• Autonomous Navigation In Agriculture
• Eye-in-hand Camera Systems
• Visual Servoing
• Robotic Pest Inspection

Statement dc:rights

• Copyright 2025 Poojan Shah

Language dc:language

en, eng

Handle dc:identifier

https://hdl.handle.net/2142/129970

OAI record oai:identifier

https://www.ideals.illinois.edu/oai-pmh?verb=GetRecord&metadataPrefix=etdms&identifier=oai%3Awww.ideals.illinois.edu%3A2142%2F129970