Robotics in high tunnel agriculture: perception-driven harvesting and crop monitoring in unstructured environments
Shah, Poojan Kalpeshbhai
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https://hdl.handle.net/2142/129970
Description
Title
Robotics in high tunnel agriculture: perception-driven harvesting and crop monitoring in unstructured environments
Author(s)
Shah, Poojan Kalpeshbhai
Issue Date
2025-07-21
Director of Research (if dissertation) or Advisor (if thesis)
Krishnan, Girish
Department of Study
Mechanical Sci & Engineering
Discipline
Mechanical Engineering
Degree Granting Institution
University of Illinois Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
Agricultural Robotics
Robotic Harvesting
Autonomous Navigation In Agriculture
Eye-in-hand Camera Systems
Visual Servoing
Robotic Pest Inspection
Language
eng
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. 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.
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