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Modeling and identification of wheel-soil interaction for precision agriculture robotics

Vito Vattiata

Modeling and identification of wheel-soil interaction for precision agriculture robotics.

Rel. Alessandro Rizzo, Antonio Petitti. Politecnico di Torino, Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica), 2020

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The utilization of unmanned ground vehicles (UGV) is spreading on agricultural applications. However, deformable terrains pose critical challenges to ground mobile robots, both in terms of energy consumption and attitude control. For this reason, current researches are devoted to improving the power consumption rate and tractive efficiency of intelligent tractors to better perform agricultural operations and to reduce energy expenditure. In order to achieve these requirements, it is necessary to analyze the soil-wheel interaction mechanics and to estimate terrain parameters to be used in predictive control systems. The main objective of this thesis is to fast prototyping a terramechanics-based wheel–soil interaction model by means of polynomial approximation of stresses originating along the contact patch. Then, a vehicle dynamic simulation is performed by applying at each wheel the forces calculated from terramechanics-based models (TBM). Moreover, the bulldozing resistance phenomenon, arising during steering maneuvers, is also taken into account. Lastly, the identification of soil parameters is carried out through a decoupled analysis of equations by linearizing the stresses during the interaction. This method allows to fastly identify soil parameters and it can be used, for example, for real-time applications. The identification process is tested by providing data from the simulation of the TBM model. However, it has not been possible to validate the model by means of real-world measured data. Finally, results are discussed and new developments involving further research are mentioned.

Relators: Alessandro Rizzo, Antonio Petitti
Academic year: 2020/21
Publication type: Electronic
Number of Pages: 94
Corso di laurea: Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica)
Classe di laurea: New organization > Master science > LM-25 - AUTOMATION ENGINEERING
Aziende collaboratrici: CNR STIIMA BARI
URI: http://webthesis.biblio.polito.it/id/eprint/16627
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