A Unified Framework for Constrained Visual-Inertial Navigation with Guaranteed Convergence

This Thesis focuses on some challenging problems in applied Computer Vision: motion estimation of a vehicle by fusing measurements coming from a low-accuracy Inertial Measurement Unit (IMU) and a Stereo Vision System (SVS), and the robust motion estimation of an object moving in front of a camera by using probabilistic techniques. In the first problem, a vehicle supposed moving in an unstructured environment is considered. The vehicle is equipped with a stereo vision system and an inertial measurements unit. For the purposes of the work, unstructured environment means that no prior knowledge is available about the scene being observed, nor about the motion. For the goal of sensor fusion, the work relies on the use of epipolar constraints as output maps in a loose-coupling approach of the measurements provided by the two sensor suites. This means that the state vector does not contain any information about the environment and associated keypoints being observed and its dimension is kept constant along the whole estimation task. The observability analysis is proposed in order to define the asymptotic convergence properties of the parameter estimates and the motion requirements for full observability of the system. It will be shown that the existing techniques of visual-inertial navigation that rely on (features-based) visual constraints can be unified under such convergence properties. Simulations and experimental results are summarized that confirm the theoretical conclusions. In the second problem, the motion estimation algorithm takes advantage from the knowledge of the geometry of the tracked object. Similar problems are encountered for example in the framework of autonomous formation flight and aerial refueling, relative localization with respect to known objects and/or patterns, and so on. The problem is challenged with respect to the classical literature, because it is assumed that the system does not know a priori the association between measurements and projections of the visible parts of the object and reformulates the problem (usually solved via algebraic techniques or iterative optimizations) into a stochastic nonlinear filtering framework. The system is designed to be robust with respect to outliers contamination in the data and object occlusions. The approach is demonstrated with the problem of hand palm pose estimation and motion tracking during reach-and-grasp operations and the related results are presented

Modellazione e Controllo di un Velivolo di tipo Quadrotor

L'elaborato affronta il problema della modellazione, identificazione e controllo di assetto di un velivolo reale di tipo Quadrotor. Nel primo capitolo vengono introdotte le equazioni non lineari che regolano il sistema e la loro linearizzazione per piccole variazioni angolari attorno al punto di lavoro; inoltre viene presentato il setup del sistema di interfacciamento fra controllore implementato su Simulink ed il sistema radiocomando/ricevitore che pilota i motori cc del velivolo. Nel secondo capitolo, dopo aver accennato la teoria del filtro di Kalman e discusso della sua implementazione per la stima dello stato del velivolo, si introducono le problematiche incontrate durante la prima sintesi del controllore sul sistema reale e le sostanziali differenze fra le simulazioni numeriche e il reale comportamento del sistema. Si stabilisce, inoltre, come tali problematiche abbiano condotto alla procedura di identificazione, della quale si discute nel terzo capitolo. Nel terzo capitolo e' dettagliata e motivata la procedura di indentificazione in frequenza e parametrica del velivolo, in condizioni classiche di volo in "hovering". L'identificazione e' stata fatta in anello aperto e ha riguardato le funzioni di trasferimento fra le velocita' angolari (in assi corpo) desiderate e quelle effettivamente misurate dai sensori. Tale procedura ha messo in evidenza la natura accoppiata delle dinamiche di roll, pitch, yaw e ha fornito una descrizione piu' accurata della dinamica e dell'elettronica di bordo del velivolo; nel capitolo, inoltre, si discute della possibilità di miglioramento dell'algoritmo di stima basato sul filtro di kalman, il quale può essere esteso con la dinamica stimata del velivolo. Nel quarto capitolo si presenta la sintesi del controllore robusto alle incertezze di modellazione, facendo ricorso a metodi di sintesi in frequenza, mediante diagrammi di Bode. L'elaborato si chiude con le considerazioni e le conclusioni circa le difficolta' incontrate e i miglioramenti ottenuti

A nonlinear complementary filter for underwater navigation using inertial measurements

This paper describes a nonlinear complementary filter capable of estimating the course motion variables namely the position, velocity, heading and accelerometers bias of an agile, over-actuated AUV during underwater operations, using the inertial sensors (IMU), the DVL, the depth sensor and the compass. The proposed work is within the framework of the V-Fides project, co-funded by Tuscany Region (Italy) and developed by a team lead by WASS S.p.A. (Whitehead Sistemi Subacquei, Livorno). The aim of the project was to develop and evaluate an high-depth, over-actuated, long endurance Autonomous Underwater Vehicle (AUV). The paper proposes the mathematical development of the observer, together with some experimental results, able to demonstrate the capabilities of the estimation scheme, compared with the estimations obtained via a standard Kalman Filter

Development of a navigation algorithm for autonomous underwater vehicles

In this paper, the authors present an underwater navigation system for Autonomous Underwater Vehicles (AUVs) which exploits measurements from an Inertial Measurement Unit (IMU), a Pressure Sensor (PS) for depth and the Global Positioning System (GPS, used during periodic and dedicated resurfacings) and relies on either the Extended Kalman Filter (EKF) or the Unscented Kalman Filter (UKF) for the state estimation. Both (EKF and UKF) navigation algorithms have been validated through experimental navigation data related to some sea tests performed in La Spezia (Italy) with one of Typhoon class vehicles during the NATO CommsNet13 experiment (held in September 2013) and through Ultra-Short BaseLine (USBL) fixes used as a reference (ground truth). Typhoon is an AUV designed by the Department of Industrial Engineering of the Florence University for exploration and surveillance of underwater archaeological sites in the framework of the Italian THESAURUS project and the European ARROWS project. The obtained results have demonstrated the effectiveness of both navigation algorithms and the superiority of the UKF (very suitable for AUV navigation and, up to now, still not used much in this field) without increasing the computational load (affordable for on-line on-board AUV implementation)

Fusing Acoustic Ranges and Inertial Measurements in AUV Navigation: the Typhoon AUV at CommsNet13 Sea Trial

The paper presents some experimental results of autonomous underwater navigation, based on the fusion of acoustic and inertial measurements. The work is in the framework of the Thesaurus project, funded by the Tuscany Region, aiming at developing techniques for systematic exploration of marine areas of archaeological interest through a team of Autonomous Underwater Vehicles (AUVs). The test was carried out with one Typhoon vehicle, a 300m depth rated AUV with acoustic communication capabilities, during the CommsNet13 experiment, organized and scientifically coordinated by the NATO S&T Org. Ctr. for Maritime Research and Experimentation (CMRE, formerly NURC), with the participation of several research institutions. The fusion algorithm is formally casted into an optimal stochastic filtering problem, where the rough estimation of the vehicle position, velocity and attitude, are refined by using the depth measurement, the relative measurements available on the acoustic channel and the vehicle surge speed

Dada 1916. La nascita dell'antiarte

Volume realizzato in occasione della mostra su Dada, a cento anni dalla nascita del movimento. L'esposizione, realizzata dai Musei di Brescia, nella sede di Santa Giulia, ha raccolto oltre duecento opere e documenti da musei e collezioni italiane e svizzere

Information-driven cooperative distributed motion planning for long range search over marine areas

This work aims at proposing a method for building a map of a priori percentage density of expected findings over an area from historical qualitative information and at defining a cooperative distributed exploration algorithm guided by the minimization of the information gain over the a priori map. The exploration algorithm is implemented by partitioning the area with the Equitable Power Diagrams theory, through potential functions for motion planning and taking into account communication constraints. Simulations are carried out using the available archaeological data base of the Tuscan Archipelago, Northern Tyrrhenian Sea, and assuming that the exploration payload in each vehicle is a side scan sonar. The algorithm is compared with a standard systematic search strategy, based on regular transects over the area, and with the Rapidly Exploring Random Tree (RTT) planning approach which exploits the same a priori information as our algorithm