Politecnico di Torino (logo)

Automated driving for a UGV for agriculture 4.0

Mohammadreza Beygifard

Automated driving for a UGV for agriculture 4.0.

Rel. Fabrizio Dabbene, Davide Ricauda Aimonino, Martina Mammarella. Politecnico di Torino, Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica), 2020

PDF (Tesi_di_laurea) - Tesi
Licenza: Creative Commons Attribution Non-commercial No Derivatives.

Download (9MB) | Preview

This thesis report presents an approach to create autonomy for a mobile robot and then focuses on the planning module of the autonomous mobile robot. Dipartimento di Scienze Agrarie, Forestali e Alimentari, DISAFA, of Universita` di Torino has developed a 4WS mobile robot and I was honored to work in a team under the supervision of Dr. Fabrizio Dabbene and Dr. Martina Mammarella of Consiglio Nazionale delle Ricerche, CNR, and Prof. Davide Ricauda Amionino of DISAFA to complete my thesis on developing an automated driving module for the robot. This study, at first, aimed to understand the needed modules to create autonomy for a mobile robot which we discussed in chapter 1. After performing a literature review we have chosen our so-called Autonomy Hierarchy. As studying each module of the hierarchy needs more effort than a single project, we decided to study the first module that is needed for autonomy and that is the motion planning module which is discussed in detail in chapter 2. Our motion planning aimed to generate a feasible and optimal path for the robot. After studying the literature, presented in chapter 2, we decided to choose the DWA technique for our path planner as it is a receding horizon technique and can generate a path that is a good reference for the motion control module of the robot, which is the second important module to control a mobile robot, which my colleague Simone Scivoli worked on it. To generate a feasible path a path planner should respect the kinematic constraints of the robot. The so-called kinematic model is a mathematical description of those constraints and we discussed its derivation and implementation in chapter 3. As the DWA technique has an intrinsic possibility to get stocked in the local minimum we studied the division of the planning module to global path planner and local path planner. The RRT* technique showed fast and reliable results in the previous studies at the literature we decided to choose this technique as our global path planner to guide our local path planner and to avoid getting stocked in the local minimum. The related literature review and our criterion to choose RRT* are discussed in detail in chapter 4. After passing the first tests that were discussed in detail in chapters 4 and 5 and tuning the cost function of both planners we planned final tests for our planner module to study its robustness and performance in different scenarios. In chapter 6 we discussed those scenarios that were challenging for a mobile robot to plan a path in them. We studied also different computation loads for our planner to test its performance in different modes. Finally, we provided an efficient, fast, and optimal planner module that can be used for our mobile robot and any other mobile robot which has a 4WS wheel based locomotion.

Relators: Fabrizio Dabbene, Davide Ricauda Aimonino, Martina Mammarella
Academic year: 2019/20
Publication type: Electronic
Number of Pages: 55
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 - IEIIT
URI: http://webthesis.biblio.polito.it/id/eprint/15278
Modify record (reserved for operators) Modify record (reserved for operators)