Claudio Carbone
AI-driven Computer Vision Design and Implementation for a Grape Harvesting Robot.
Rel. Marco Vacca. Politecnico di Torino, Master of science program in Mechatronic Engineering, 2025
Abstract
This master’s thesis presents the design and development of an autonomous grape-harvesting robot, specifically engineered for operation in a real vineyard. The primary aim is to develop a robot that can accurately and gently harvest grapes, considering their delicate nature and need for a careful touch. The system consists of a 3-degree-of-freedom (DOF) robotic arm that positions an end effector near each grape cluster. The arm’s movements are controlled by an STM32F401RE microcontroller, which directs the motors and drivers to ensure precise placement. A key focus of the research is achieving real-time vision processing, facilitated by the robot’s central unit, an Nvidia Jetson Orin Nano board.
This board was chosen for its optimized computer vision capabilities, managing both the process state machine and neural network inference to detect objects, such as grape clusters, through a connected camera
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