Virtual sensing technology applied to a swarm of autonomous robots.

This thesis proposes a novel technology in the field of swarm robotics that allows a swarm of robots to sense a virtual environment through virtual sensors. Virtual sensing is a desirable and helpful technology in swarm robotics research activity, because it allows the researchers to efficiently and quickly perform experiments otherwise more expensive and time consuming, or even impossible. In particular, we envision two useful applications for virtual sensing technology. On the one hand, it is possible to prototype and foresee the effects of a new sensor on a robot swarm, before producing it. On the other hand, thanks to this technology it is possible to study the behaviour of robots operating in environments that are not easily reproducible inside a lab for safety reasons or just because physically infeasible. The use of virtual sensing technology for sensor prototyping aims to foresee the behaviour of the swarm enhanced with new or more powerful sensors, without producing the hardware. Sensor prototyping can be used to tune a new sensor or perform performance comparison tests between alternative types of sensors. This kind of prototyping experiments can be performed through the presented tool, that allows to rapidly develop and test software virtual sensors of different typologies and quality, emulating the behaviour of several hardware real sensors. By investigating on which sensors is better to invest, a researcher can minimize the sensors’ production cost while achieving a given swarm performance. Through augmented reality, it is possible to test the performance of the swarm in a desired virtual environment that cannot be set into the lab for physical, logistic or economical reasons. The virtual environment is sensed by the robots through properly designed virtual sensors. Virtual sensing technology allows a researcher to quickly carry out real robots experiment in challenging scenarios without all the required hardware and environment.

Studio di componenti commerciali per sensing induttivo

Questa tesi ha lo scopo di indagare un particolare circuito commerciale che può connettersi con un sensore induttivo: l'LDC1000. Vi sono elencate e spiegate tutte le caratteristiche e le modalità di funzionamento con i link dove è possibile scaricare tutta la documentazione ufficiale del costruttore

Compressed sensing in digital tomosynthesis reconstruction

In this work we study a model for the breast image reconstruction in Digital Tomosynthesis, that is a non-invasive and non-destructive method for the three-dimensional visualization of the inner structures of an object, in which the data acquisition includes measuring a limited number of low-dose two-dimensional projections of an object by moving a detector and an X-ray tube around the object within a limited angular range. The problem of reconstructing 3D images from the projections provided in the Digital Tomosynthesis is an ill-posed inverse problem, that leads to a minimization problem with an object function that contains a data fitting term and a regularization term. The contribution of this thesis is to use the techniques of the compressed sensing, in particular replacing the standard least squares problem of data fitting with the problem of minimizing the 1-norm of the residuals, and using as regularization term the Total Variation (TV). We tested two different algorithms: a new alternating minimization algorithm (ADM), and a version of the more standard scaled projected gradient algorithm (SGP) that involves the 1-norm. We perform some experiments and analyse the performance of the two methods comparing relative errors, iterations number, times and the qualities of the reconstructed images. In conclusion we noticed that the use of the 1-norm and the Total Variation are valid tools in the formulation of the minimization problem for the image reconstruction resulting from Digital Tomosynthesis and the new algorithm ADM has reached a relative error comparable to a version of the classic algorithm SGP and proved best in speed and in the early appearance of the structures representing the masses.

Sviluppo di un firmware per un sistema di sensing impedenziometrico a bassa potenza

Il progetto vuole realizzare un sistema ultra low power, in grado di monitorare variabili fisiche quali temperatura e conducibilità dell'acqua nelle profondità marine in autonomia, per una durata complessiva di due anni. Il salvataggio dei dati raccolti nel periodo di utilizzo avrà come fine ultimo lo studio dei cambiamenti climatici relativi all'ambiente marino. Volendo collocare il sistema di monitoraggio sul dorso di pesci o in profondità oceaniche non facilmente accessibili è necessario garantire dimensioni ridotte e un funzionamento autonomo duraturo al termine del quale sarà possibile scaricare i dati raccolti. Nel tentativo di rispettare la specifica relativa al ciclo di lavoro autonomo del sistema è stato importante adottare una politica rigorosa riguardante i consumi estremamente ridotti, senza però venir meno alle ulteriori specifiche di progetto, riportate in dettaglio nei paragrafi successivi. Dalla progettazione circuitale alla realizzazione del firmware, passando per una minuziosa scelta della componentistica a minor consumo, ho avuto la possibilità di dar vita all'intero progetto in autonomia, confrontandomi con tutti gli aspetti e le problematiche che la realizzazione di un simile progetto porta con se.