Matteo Sperti
Non-linear Model Predictive Control for GPS-free Autonomous Navigation in Vineyards.
Rel. Marcello Chiaberge, Marco Ambrosio, Mauro Martini, Alessandro Navone, Andrea Ostuni. Politecnico di Torino, Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica), 2023
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Abstract
Precision agriculture has made significant progress in recent years by utilizing technology to optimize crop production, enhance farming efficiency, and automate harvesting processes. Autonomous navigation is a critical component for ground rovers in the agricultural field. This thesis focuses on developing an advanced autonomous navigation system for a rover operating within row-based crops. A position-agnostic system is proposed to address the challenging situation when standard localization methods, like GPS, fail due to unfavorable weather or obstructed line-of-sight. This breakthrough is especially vital in densely vegetated regions, including areas covered by thick tree canopies or pergola vineyards. The primary objective of the control system is to navigate through entire rows, effectively avoiding obstacles in its path.
To ensure versatility across crop types with different row spacing, the rover is designed to operate within the entire inter-row area for crops with small row spacing or predefined lanes for crops with larger ones
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