Integration of the computer controlled screwdriver for Robotic manufacturing in the ROS environment

The computer controlled screwdriver is a modern technique to perform automatic screwing/unscrewing operations.The main focus is to study the integration of the computer controlled screwdriver for Robotic manufacturing in the ROS environment.This thesis describes a concept of automatic screwing mechanism composed by universal robots, in which one arm of the robot is for inserting cables and the other is for screwing the cables on the control panel switch gear box. So far this mechanism is carried out by human operators and is a fairly complex one to perform, due to the multiple cables and connections involved. It's for this reason that an automatic cabling and screwing process would be highly preferred within automotive/automation industries. A study is carried out to analyze the difficulties currently faced and a controller based algorithm is developed to replace the manual human efforts using universal robots, thereby allowing robot arms to insert the cables and screw them onto the control panel switch gear box. Experiments were conducted to evaluate the insertion and screwing strategy, which shows the result of inserting and screwing cables on the control panel switch gearbox precisely.

Eco-sistemi informatici, distribuiti, real-time, a supporto del lavoro cooperativo in scenari di emergenza: Studio e realizzazione di un caso applicativo

I sistemi software nati dall'esigenza di supportare agevolmente ed efficacemente il lavoro cooperativo, in particolare quelli orientati al supporto di azioni di soccorso in scenari di emergenza, appaiono tutt'ora fortemente limitati e frammentati. In molti casi vengono affrontate solamente specifiche dimensioni del problema complessivo, anche se il livello al quale è giunto lo sviluppo tecnologico e i risultati osservati in ambito di ricerca permettono di delineare soluzioni complete e significative per l'impiego in ambiti reali. Tale tipologia di sistemi è stata scelta per il grande interesse che desta sia dal punto di vista accademico, essendo costituita da molteplici sotto--sistemi spesso eterogenei che debbono necessariamente interagire e supportare l'azione umana, sia dal punto di vista industriale, interpretando la necessità crescente di iniettare nel maggior numero possibile di livelli sociali la forte dipendenza (il supporto allo stesso tempo) dalle scienze tecnologiche ed informatiche, per rafforzare e talvolta estendere le possibilità dell'essere umano in quanto tale. Dopo una prima fase in cui verrà delineato un quadro concettuale piuttosto dettagliato circa i principali elementi e problematiche che caratterizzano la classe di sistemi considerati, sarà dato spazio alla validazione di tali principi e considerazioni emerse, confrontandosi con la progettazione e sviluppo in forma prototipale di un sotto--sistema relativo ad un caso di studio reale, significativo per l'ambito di applicazione, nato dalla collaborazione con l'Università degli Studi di Bologna di un'azienda della regione Emilia--Romagna. Il sistema software realizzato vuole essere innanzi tutto la risposta alle esigenze emerse nel caso di studio trattato, in modo tale da potersi sostituire agli attuali limitati supporti alla cooperazione, ma anche un esperimento che possa essere considerato un artefatto centrale da utilizzare come base di conoscenza condivisa, in cui vengano fattorizzati i concetti e meccanismi chiave, fondamentali per sviluppi futuri.

Distributed non-cooperative robust economic predictive control for dynamically coupled linear systems.

In this thesis, a tube-based Distributed Economic Predictive Control (DEPC) scheme is presented for a group of dynamically coupled linear subsystems. These subsystems are components of a large scale system and control inputs are computed based on optimizing a local economic objective. Each subsystem is interacting with its neighbors by sending its future reference trajectory, at each sampling time. It solves a local optimization problem in parallel, based on the received future reference trajectories of the other subsystems. To ensure recursive feasibility and a performance bound, each subsystem is constrained to not deviate too much from its communicated reference trajectory. This difference between the plan trajectory and the communicated one is interpreted as a disturbance on the local level. Then, to ensure the satisfaction of both state and input constraints, they are tightened by considering explicitly the effect of these local disturbances. The proposed approach averages over all possible disturbances, handles tightened state and input constraints, while satisfies the compatibility constraints to guarantee that the actual trajectory lies within a certain bound in the neighborhood of the reference one. Each subsystem is optimizing a local arbitrary economic objective function in parallel while considering a local terminal constraint to guarantee recursive feasibility. In this framework, economic performance guarantees for a tube-based distributed predictive control (DPC) scheme are developed rigorously. It is presented that the closed-loop nominal subsystem has a robust average performance bound locally which is no worse than that of a local robust steady state. Since a robust algorithm is applying on the states of the real (with disturbances) subsystems, this bound can be interpreted as an average performance result for the real closed-loop system. To this end, we present our outcomes on local and global performance, illustrated by a numerical example.

Distributed collision-free traffic management via vertex cover for multi-vehicle systems

In this thesis, we state the collision avoidance problem as a vertex covering problem, then we consider a distributed framework in which a team of cooperating Unmanned Vehicles (UVs) aim to solve this optimization problem cooperatively to guarantee collision avoidance between group members. For this purpose, we implement a distributed control scheme based on a robust Set-Theoretic Model Predictive Control ( ST-MPC) strategy, where the problem involves vehicles with independent dynamics but with coupled constraints, to capture required cooperative behavior.