Semantic Obstacle Avoidance of Robotic Arm for Fruit Harvesting
Daniele Tanda
Semantic Obstacle Avoidance of Robotic Arm for Fruit Harvesting.
Rel. Marcello Chiaberge. Politecnico di Torino, Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica), 2024
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Abstract
With the technological progress of robotics, Artificial Intelligence and vision systems, the projects and applications that regard the automation of simple and repetitive tasks are spreading, and, from a business point of view, business owners are more interested in automating activities for which it is difficult to find personnel. Moreover, Fruit Harvesting heavily relies on intensive human labor and sometimes it can be physically challenging. These considerations, together with the need to decrease the cost of the harvesting task (the most expensive regarding fruit agriculture), leads to the development of solutions that involve the help of automation. Despite the efforts of the actual research in robotics, the main issue of this kind of system is that machines and robotic systems need to reach a high level of complexity in order to behave and execute a series of tasks that a human would perform unconsciously and with a certain dexterity (for example the collision avoidance of the arm with the environment).
The solution proposed in this work is an automated fruit harvesting system employing a manipulator placed on a mobile platform that moves through the orchard
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