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Archivio digitale delle tesi discusse presso l’Università di Pisa

Tesi etd-09122022-103655


Tipo di tesi
Tesi di laurea magistrale
Autore
TEPPATI LOSÈ, MASSIMO
Indirizzo email
m.teppatilose@studenti.unipi.it, massimotep@hotmail.it
URN
etd-09122022-103655
Titolo
Design and Implementation of Reactive Obstacle Avoidance System for Quadrotors ​
Dipartimento
INGEGNERIA DELL'INFORMAZIONE
Corso di studi
INGEGNERIA ROBOTICA E DELL'AUTOMAZIONE
Relatori
relatore Prof. Avizzano, Carlo Alberto
relatore Dott. Satler, Massimo
relatore Ing. Mugnai, Michael
Parole chiave
  • obstacle avoidance
  • stereo vision
  • uav
Data inizio appello
29/09/2022
Consultabilità
Tesi non consultabile
Riassunto
Autonomous multirotor aerial vehicles have great potential to address and optimize solutions for many fields of applications. One of the essential requirements that characterize the architecture of an autonomous vehicle is the local path planner. This module is in charge of detecting and avoiding obstacles during navigation by acquiring sensor information from the surrounding 3D environment and computing collision-free path in real-time.
In this thesis, a three-dimensional collision avoidance algorithm has been implemented and tested in different unknown environments. After studying the advantages and disadvantages of algorithms in the literature, the 3DVFH+ algorithm has been chosen and implemented on a quadrotor equipped with a stereo-vision camera. The reactive control architecture allows the UAV to safely avoid obstacles during a mission plan with real-time sensor data. The algorithm has been developed in the ROS framework using software-in-the-loop paradigm. The effectiveness of the designed solution has been tested in Gazebo simulation environments where all the algorithm parameters tuning has been performed. Then experimental tests on a real quadrotor vehicle have also been done to prove both the feasibility of the proposed solution on a limited resources platform and the capability to work in real-life scenarios subjected to sensor noise. The proposed solution was also applied for the ICUAS 2022 UAV Competition, winning third place in the final phase.
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