Adriana Di Terlizzi
Instance Segmentation and Visual Servoing for apple harvesting.
Rel. Marcello Chiaberge, Mauro Martini, Alessandro Navone, Marco Ambrosio. Politecnico di Torino, Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica), 2024
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Abstract
In recent years, the rising global population and the growing demand for food, coupled with a shortage of human laborers, have placed immense pressure on the agricultural sector to revolutionize farming operations through advanced technology, to produce more food, more efficiently and sustainably. In this context, autonomous harvesting robots have emerged as a promising solution to these challenges. This thesis focuses on designing a visual servo for apple harvesting using the Kinova Gen3 Lite, a 6 Degrees of freedom (DoF) manipulator, equipped with an Intel RealSense D435i camera mounted on its end effector. The objective is to enable the robot to accurately identify the target apple and autonomously guide the robot tool toward it for successful grasping.
To address the problems, the proposed solution comprises two main modules: one dedicated to visual perception and another focused on manipulator control
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