|Tipo di tesi||Tesi di dottorato di ricerca|
|Titolo||Nuove Tecniche di Stima e Controllo per Robot Mobili nel Mondo Reale|
|Titolo in inglese||New Estimation and Control Techniques for Real World Mobile Robots|
|Settore scientifico disciplinare||ING-INF/04 - AUTOMATICA|
|Corso di studi||Scuola di D.R. in INGEGNERIA DELL'INNOVAZIONE INDUSTRIALE|
|Data inizio appello||2014-04-11|
|Disponibilità||Accessibile via web (tutti i file della tesi sono accessibili)|
Questa tesi tratta del trasferimento tecnologico delle più recenti scoperte nel settore della robotica mobile in applicazioni industriali e di servizio nel mondo reale. Nello specifico, le ricerche presentate sono state svolte nel framework di due progetti: il progetto DiRò e il progetto REMOCAL.
This thesis deals with the technology transfer of the most recent findings in the mobile robotics field into applications into real world industries and service applications. Specifically the presented research has been done in the framework of two projects: DiRò and REMOCAL. The main scope of the DiRò (Distretto della Robotica Mobile) project is to create a collaboration between companies of the province of Reggio Emilia with the objective to develop new solution in the framework of the Mobile Robotics. This thesis focuses mainly on three development objectives of this project. First the design of a smart autonomous lawnmower, and in particular its localization algorithm, is described in this thesis. The robot uses a particular implementation of the Extended Kalman Filter (EKF) for localizing itself in the garden. Then a novel navigation strategy has been implemented, in order to make the robot doing its mowing task ensuring a complete and even coverage of the assigned working area. Then the characterization of 3D sensors is discussed. In particular a comparison between a stereo–camera (a Bumblebee2 stereo–camera) and an RGB–D sensor (the Microsoft Kinect) is presented. Then the performance of the two sensors is tested through a localization algorithm based on an EKF. The Dir`o project discussion eventually ends with the design of a novel lead–acid batteries State of Charge (SoC) estimator also based on the EKF algorithm. Finally the REMOCAL (Robotic Equipment for Measuring by Optics Calibrator) project is described. The project consists of the design and the realization of a mobile robot able to autonomously calibrate a car tyres convergence measurement device. In this manuscript both the mechanical design of the robot and the development of the software which controls the robot are reported.