Master's Thesis Completed Projects

Person tracking methodologies and algorithms in service robotic applications

Candidate:  Anna Boschi
Supervisor: Prof. Marcello Chiaberge
Date: October 2019

The vital statistics of the last century highlight a sharply increasement of the average life of the world population with a consequent growth of the number of elderly people. This scenario has caused new social needs that the research in the service robotics field is trying to fulfill. Particularly, the idea of this thesis is born at the PIC4SeR (PoliTo interdepartmental centre for service robotics) with the purpose of creating complex service robotics applications to support the autonomous and selfsufficient old people into their house in everyday life, avoiding the task of monitoring them by third parties. This work represents the first steps of a broad project in which many other service tasks will be integrated.
The main argument of this thesis is to develop algorithms and methodologies to detect, track and follow a person in an indoor environment using a small wheeled rover and low cost and available sensors to monitor the target person. Several techniques are explored showing the evolution of these methods along the years: from the classical Machine Learning algorithms to the Deep Neural Network ones. Since the main requirement to be respected is the necessity of real-time results, only few of the analysed algorithms are developed for this project scope and at the end are compared in order to find the best solution with optimal outcomes. The detection and localization are the basis of the person tracking application, done by the robot on which it has been implemented a movement control algorithm and at last it has been introduced an obstacle avoidance algorithm to prevent collisions.

Comparison of Stereo Visual Inertial Odometry Algorithms for Unmanned Ground Vehicles

Candidate:  Roberto Cappellaro
Supervisor: Prof. Marcello Chiaberge
Date: July 2019

PIC4SeR is the Interdepartmental center of PoliTO for service robotics. For its research it emerged the need to investigate indoor localization algorithms, in particular the visual-inertial type. This work aims to study different types of algorithms to assess which one is the best choice for indoor localization with the already available COTS hardware. Although the end application is meant to be UAV, a Jackal UGV is used instead, because it was the vehicle available and it lowered the risks of damages during the testing phase. A MYNTYEYE S stereo camera, with included IMU and IR projector, was available and mounted on the UGV. Three algorithms are considered: a light-weight filter-based VIO framework, ROVIO, and two optimization-based VIO frameworks, VINS-Fusion and OKVIS, that should better accommodate data asynchrony. The algorithms are tested in two different environments making the robot follow two paths multiple times: a linear path in a corridor and a pseudo-rectangular one in a room. The algorithms performance is evaluated by two parameters: the relative error on the total travelled distance and the difference between initial and final position of the UGV. The tests underlined no best algorithm, but a dependence on the environment. As future work, it would be interesting to test a camera using a tight hardware-synchronization with an IMU, since, according to the literature, should be a big source of error.

Remote Monitoring of Robots using Web Based Technologies and ROS Framework

Candidate:  Angelo Tartaglia 
Supervisor: Prof. Marcello Chiaberge
Date: October 2018

World population is growing faster than expected. Every year Earth resources are consumed faster, as proven by the early fall of the Earth Overshoot Day that claims the end of year resources. One of the simplest solutions to this problem would be investing in technologies and innovations towards a smart extraction of what population needs. In the last few years a lot of companies introduced automation and robots to improve production in terms of time and obviously cost. Agricultural world is not distant from this evolution; in fact many of the works attempted are now helped by a set of machines that simplifies human work. Hitherto the application in precision agriculture has been always under the human control; there are a lot of applications that see the participation of a worker and in parallel a machine used for a lot of tasks. In the future may an entire field will be managed by a group of automated robots that work together. Those machines will require a lot of specific features likes autonomous navigation, mapping, visual object recognition and many others. This thesis is part of that project and it regards the detection andclassificationoffruitsforfutureapplicationofauto-harvestingandhealthcontrol. Inamorespecificway apples will be considered in this thesis work for fruit application and methods and algorithms as Y.O.L.O. and Mask R-CNN to do the processing of images will be described.These techniques permits the detection of apples in post processing and in real-time with accuracies that range over 32% to 78%. The final result can be used in future applications for spatial localization of fruits and for the detection of possible diseases. It should be emphasised that, even if the thesis shows the results of the object class apple, the algorithms can be applied in a wide range of objects with the only requirement of a different training images dataset. 

Real-time Monitoring of Robotic Devices by using Smartphones Sensors and the ROS Framework

Candidate:  Davide Brau
Supervisor: Prof. Enrico Masala
Date: Aprile 2019

Nell’ambito della robotica, l’attività di monitoraggio risulta fondamentale per il funzionamento dell’intero sistema, sia esso controllato da un essere umano o da un algoritmo programmato per decidere in maniera autonoma. In questo contesto, con monitoraggio si intende quel processo continuo, o svolto a intervalli regolari, che ha lo scopo di acquisire le informazioni provenienti dalle varie parti del sistema robotico, nello specifico i sensori, utili per poter esercitare un controllo efficace su di esso. Durante questa attività di tesi, l’obbiettivo è stato quello di esplorare le possibilità e le soluzioni adatte a svolgere il monitoraggio, analizzando le funzionalità del frame-work: ROS. Per fare ciò, è stato necessario capire la logica utilizzata all’interno di quest’ultimo nell’interfacciarsi con i vari moduli, ponendo particolare enfasi sull’infrastruttura di comunicazione e sui formati utilizzati per i dati; focalizzandosi in seguito su quelli multimediali, in particolare le immagini. In seguito, si è cercato di mettere in pratica le nozioni acquisite, attraverso lo sviluppo di un’applicazione Android basata su ROS che ha lo scopo di fornire un supporto concreto al monitoraggio remoto. Essa consente di acquisire una grande varietà di informazioni, grazie ai vari sensori presenti sui dispositivi odierni, utili per fornire un supporto aggiuntivo e a basso costo per le operazioni di controllo, nel momento in cui lo smartphone viene messo a bordo di un qualsiasi tipo di drone o rover. Si è quindi cercato di evidenziare le varie criticità dovute sia ai limiti computazionali e di reattività tipici dei dispositivi mobili, sia alle caratteristiche della rete. Questi elementi possono determinare un aumento delle latenze o la perdita dei dati, tollerabili entro un certo limite, nel caso di controllo real-time. Attualmente, l’applicazione consente di acquisire informazioni relative alla cinematica utilizzando: accelerometro, giroscopio, magnetometro e il servizio di localizzazione. Tuttavia, il monitoraggio può anche coinvolgere l’ambiente circostante in cui il robot si muove, per tale motivo vengono acquisiti i dati riguardanti: temperatura, pressione e illuminamento; oltre ad informazioni relative alla rete cellulare, al Wi-Fi e alla batteria. L’applicazione consente anche la visualizzazione da remoto delle immagini acquisite dalle fotocamere utilizzando le codifiche: JPEG e H264. Inoltre, sono stati definiti i vari ROS Service che permettono di regolare i parametri associati ad esse. Durante la fase di sviluppo, sono stati introdotti nuovi tipi di messaggi ROS per il trasporto di informazioni associate alle classi Android, tra cui quelli specifici per il GNSS. È stato possibile sfruttare questi ultimi per la condivisione e l’elaborazione di un insieme di informazioni dettagliate ottenute dai satelliti, note con il nome di “raw measurements” (disponibili negli smartphone più recenti). Questi, se utilizzati in modo appropriato, potrebbero costituire una nuova frontiera nello sviluppo di applicazioni per il posizionamento ad alta precisione, dalle quali molti sistemi robotici potrebbero trarre grande vantaggio. Infine, l’ultima parte ha riguardato le prove con il rover Clearpath Jackal, queste si sono rivelate particolarmente utili per poter verificare in un contesto reale le difficoltà e i limiti che ci ritrova a dover affrontare nello sviluppo di questo tipo di applicazioni.

Machine Learning Algorithms for Service Robotics Applications in Precision Agriculture

Candidate:  Federico Barone 
Supervisor: Prof. Enrico Masala
Date: Aprile 2019

La robotica rappresenta uno dei settori disciplinari maggiormente in crescita nel mondo della ricerca tecnologica. In particolare, la robotica di servizio spicca tra i vari ambiti che studiano tale disciplina. Il presente elaborato si pone l’obiettivo di realizzare un’applicazione web che sia in grado di interagire con un robot da remoto. Questa permette sia di controllare i movimenti effettuati dal robot che le sue potenzialità. Di fatto, il robot presenta alcune caratteristiche dalle quali è possibile ricavare molteplici informazioni, tra cui, principalmente, la sua posizione. Inoltre, mediante l’utilizzo di un dispositivo android, è possibile utilizzare opportuni sensori presenti in esso gestendone i dati multimediali acquisiti. L’interfaccia web, nel suo complesso, ha lo scopo di monitorare da remoto l’ambiente circostante al robot, visualizzando i parametri in opportuni grafici bidimensionali. L’utilizzo del framework ROS (Robot Operating System) è alla base della programmazione robotica di servizio. Con l’emergere dell’Internet of Things (IoT), aumenta l’interesse nel fornire interfacce web che consentano agli utenti di monitorare i loro strumenti da remoto. Pertanto, sfruttando talune tecnologie Web Based è stato possibile realizzare uno strumento, composto dall’ambiente di configurazione ROS e dall’applicativo web, atto al monitoraggio remoto del robot. Usufruendo di uno o più dispositivi android posti sul robot, inoltre, è stato possibile monitorare e analizzare differenti parametri acquisiti dai vari sensori. Effettuando varie misurazioni mediante più dispositivi android, è stato possibile confrontare i dati acquisiti e trarne le dovute considerazioni.

Navigation Algorithms for Unmanned Ground Vehicles in Precision Agriculture Applications​

Candidate:  Jurgen Zoto 
Supervisor: Prof. Marcello Chiaberge
Date: October 2018

Robotics for agriculture can be considered a very recent application of one of the most ancient and important sectors, where the latest and most advanced innovations have been brought. Over the years, thanks to continous improvement in mechanization and automation, crop output has extremely increased, enabling a large growth in population and enhancing the quality of life around the world. Both these factors, as a consequence, are leading to a higher demand for agriculture and forestry output. Precision agriculture defined as the correct management of crops for increasing its productivity and maximizing harvest, is considered the answer to this issue. As a matter of fact, thanks to the development of portable sensors, the availability of satellite images and the use of drones, the collection of data is allowing a vast development in this field. This thesis adresses in general robotics for agriculture in the form of a solution to be applied in order to improve robot mobility, in particular automated path planning in agricultural fields, by proposing a method to classify different parcels of which they are composed and to assign a precise task to the terrestrial unmanned robot.

Obstacle Avoidance Algorithms for Autonomous Navigation System in Unstructured Indoor Areas

Candidate:  Lorenzo Galtarossa 
Supervisor: Prof. Marcello Chiaberge
Date: October 2018

This work aims to implement different autonomous navigation algorithms for Obstacle Avoidance that allow a robot to move and perform in an unknown and unstructured indoor environment.
The first step is the investigation and study of the platform, divided into software and hardware, available at the Mechatronics Laboratory (Laboratorio Interdisciplinare di Meccatronica, LIM) at the Politecnico di Torino, on which it is implemented the navigation algorithm. For what is concerned with the software platform, ROS has been used. The Robot Operating System is an open source framework to manage robots’ operations, tasks, motions. As hardware platform the TurtleBot3 (Waffle and Burger) has been used that is ROS-compatible.
The second step is the inspection of the different algorithms that are suitable and relevant for our purpose, goal and environment. Many techniques could be used to implement the navigation that is generally divided into global motion planning and local motion control. Often autonomous mobile robots work in an environment for which prior maps are incomplete or inaccurate. They need the safe trajectory that avoids the collision.
The algorithms presented in this document are related to the local motion planning; therefore, the robot, using the sensor mounted on it, is capable to avoid the obstacles by moving toward the free area.
Three different algorithms of Obstacle Avoidance are presented in this work, that address a complete autonomous navigation in an unstructured indoor environment. The algorithms grow in complexity taking into consideration the evolution and the possible different situations in which the robot will have to move, and all are tested on the TurtleBot3 robot, where only LiDAR was used as sensor to identify obstacles.
The third algorithm, “Autonomous Navigation”, can be considered the final work, the main advantage is the possibility to perform curved trajectory with an accurate choice of the selected path, combining the angular and the linear velocity (980 different motions), the LiDAR scans 180° in front of the robot to understand the correct direction. The last step is the automatic creation of the map. This map will be analysed and compared with the one defined using the RViz software that is the official software used in ROS environment. The tool is suitable to visualize the state of the robot and the performance of the algorithms, to debug faulty behaviours, and to record sensor data. The improvement of this reactive Obstacle Avoidance method is to successfully drive robots in Indoor troublesome areas. As conclusion we will show experimental results on TurtleBot3 in order to validate this research and provide an argumentation about the advantages and limitations.

Implementation of an Ultralight Autopilot Drone for Service Robotics

Candidate:  Salvatore Romano
Supervisor: Prof. Marcello Chiaberge
Date: December 2018

In this thesis, after a brief introduction on the regulation and classification of UAVs, the main sizing criteria of each component of a multirotor will be shown. Starting from the design constraints and a state of the art of the main flight controllers, the hardware and firmware components chosen for the implementation of an autopilot quadcopter under 250 grams will be described. The sizing of the components will be strongly nfluenced by the weight of each of them and will be flanked by a test on the motor / propeller coupling to evaluate the performance and then to choose the most suitable devices for the purpose. Once the Pixracer
has been identified as the best flight controller for the project, the PX4 firmware and related software for remote control (Mission Planner and QgraounControl) will be described. Finally, after the assembly phase, the evaluation tests of the performance of the aircraft, the problems encountered and the possible solutions
and improvements will be described.