Applicazione ROS 2 di un robot antropomorfo in esecuzione su container VxWorks in architettura IMA

L’elaborato di tesi discute del progetto di integrazione tra ROS 2, framework open-source per lo sviluppo di applicazioni robotiche, e VxWorks, sistema operativo in tempo reale (RTOS), attraverso l’utilizzo di container OCI compliant su VxWorks. L’integrazione è stata svolta all’interno dello stack software di IMA (Industria Macchine Automatiche). Il progetto ha dunque integrato ROS 2 Humble e VxWorks 7 permettendo l’utilizzo di costrutti software di ROS 2 su dei container in esecuzione a livello User su VxWorks. Successivamente è stata creata una applicazione di pick and place con un robot antropomorfo (Universal Robots Ur5e) avvalendosi di ROS 2 Control, framework per l’introduzione e gestione di hardware e controllori, e MoveIt 2, framework per incorporare algoritmi di motion-planning, cinematica, controllo e navigazione. Una volta progettata l’applicazione, il sistema è stato integrato all’interno dell’architettura di controllo di IMA. L’architettura a container VxWorks di IMA è stata estesa per il caso ROS 2, la comunicazione tra campo e applicazione ROS 2 è passata tramite il master EtherCAT e il modulo WebServer presenti nell’architettura IMA. Una volta eseguito il container ROS 2 posizione e velocità dei servo motori sono stati inviati tramite al WebServer di IMA sfruttando la comunicazione VLAN interna. Una volta ricevuto il messaggio, il WebServer si è occupato di trasferirlo al master EtherCAT che in aggiunta si è occupato anche di ottenere le informazioni sullo stato attuale del robot. L’intero progetto è stato sviluppato in prima battuta in ambiente di simulazione per validarne l’architettura. Successivamente si è passati all’installazione in ambiente embedded grazie all’ausilio di IPC sui quali è stato testato l’effettivo funzionamento dell’integrazione all’interno dell’architettura IMA.

Integración de Google Maps y TSP Solvers para la definición y resolución del TSP

Este trabajo final de carrera presenta la arquitectura e implementación de un entorno web para la descripción y visualización de instancias reales del TSP (Travelling Salesman Problem), a través de Google Maps, y su posterior resoluación mediante tècnicas de optimización combinatoria.

Efficient Algorithms for Coastal Geographic Problems

The increasing performance of computers has made it possible to solve algorithmically problems for which manual and possibly inaccurate methods have been previously used. Nevertheless, one must still pay attention to the performance of an algorithm if huge datasets are used or if the problem iscomputationally difficult. Two geographic problems are studied in the articles included in this thesis. In the first problem the goal is to determine distances from points, called study points, to shorelines in predefined directions. Together with other in-formation, mainly related to wind, these distances can be used to estimate wave exposure at different areas. In the second problem the input consists of a set of sites where water quality observations have been made and of the results of the measurements at the different sites. The goal is to select a subset of the observational sites in such a manner that water quality is still measured in a sufficient accuracy when monitoring at the other sites is stopped to reduce economic cost. Most of the thesis concentrates on the first problem, known as the fetch length problem. The main challenge is that the two-dimensional map is represented as a set of polygons with millions of vertices in total and the distances may also be computed for millions of study points in several directions. Efficient algorithms are developed for the problem, one of them approximate and the others exact except for rounding errors. The solutions also differ in that three of them are targeted for serial operation or for a small number of CPU cores whereas one, together with its further developments, is suitable also for parallel machines such as GPUs.

A Study of Ordered Gene Problems Featuring DNA Error Correction and DNA Fragment Assembly with a Variety of Heuristics, Genetic Algorithm Variations, and Dynamic Representations

Ordered gene problems are a very common classification of optimization problems. Because of their popularity countless algorithms have been developed in an attempt to find high quality solutions to the problems. It is also common to see many different types of problems reduced to ordered gene style problems as there are many popular heuristics and metaheuristics for them due to their popularity. Multiple ordered gene problems are studied, namely, the travelling salesman problem, bin packing problem, and graph colouring problem. In addition, two bioinformatics problems not traditionally seen as ordered gene problems are studied: DNA error correction and DNA fragment assembly. These problems are studied with multiple variations and combinations of heuristics and metaheuristics with two distinct types or representations. The majority of the algorithms are built around the Recentering- Restarting Genetic Algorithm. The algorithm variations were successful on all problems studied, and particularly for the two bioinformatics problems. For DNA Error Correction multiple cases were found with 100% of the codes being corrected. The algorithm variations were also able to beat all other state-of-the-art DNA Fragment Assemblers on 13 out of 16 benchmark problem instances.

Optimal Path Searching through Specified Routes using different Algorithms

To connect different electrical, network and data devices with the minimum cost and shortest path, is a complex job. In huge buildings, where the devices are placed at different locations on different floors and only some specific routes are available to pass the cables and buses, the shortest path search becomes more complex. The aim of this thesis project is, to develop an application which indentifies the best path to connect all objects or devices by following the specific routes.To address the above issue we adopted three algorithms Greedy Algorithm, Simulated Annealing and Exhaustive search and analyzed their results. The given problem is similar to Travelling Salesman Problem. Exhaustive search is a best algorithm to solve this problem as it checks each and every possibility and give the accurate result but it is an impractical solution because of huge time consumption. If no. of objects increased from 12 it takes hours to search the shortest path. Simulated annealing is emerged with some promising results with lower time cost. As of probabilistic nature, Simulated annealing could be non optimal but it gives a near optimal solution in a reasonable duration. Greedy algorithm is not a good choice for this problem. So, simulated annealing is proved best algorithm for this problem. The project has been implemented in C-language which takes input and store output in an Excel Workbook

Algoritmo memético com infecção viral: uma aplicação ao problema do caixeiro viajante assimétrico

The Combinatorial Optimization is a basic area to companies who look for competitive advantages in the diverse productive sectors and the Assimetric Travelling Salesman Problem, which one classifies as one of the most important problems of this area, for being a problem of the NP-hard class and for possessing diverse practical applications, has increased interest of researchers in the development of metaheuristics each more efficient to assist in its resolution, as it is the case of Memetic Algorithms, which is a evolutionary algorithms that it is used of the genetic operation in combination with a local search procedure. This work explores the technique of Viral Infection in one Memetic Algorithms where the infection substitutes the mutation operator for obtaining a fast evolution or extinguishing of species (KANOH et al, 1996) providing a form of acceleration and improvement of the solution . For this it developed four variants of Viral Infection applied in the Memetic Algorithms for resolution of the Assimetric Travelling Salesman Problem where the agent and the virus pass for a symbiosis process which favored the attainment of a hybrid evolutionary algorithms and computational viable

Algoritmo Q-learning como estratégia de exploração e/ou explotação para metaheurísticas GRASP e algoritmo genético

Techniques of optimization known as metaheuristics have achieved success in the resolution of many problems classified as NP-Hard. These methods use non deterministic approaches that reach very good solutions which, however, don t guarantee the determination of the global optimum. Beyond the inherent difficulties related to the complexity that characterizes the optimization problems, the metaheuristics still face the dilemma of xploration/exploitation, which consists of choosing between a greedy search and a wider exploration of the solution space. A way to guide such algorithms during the searching of better solutions is supplying them with more knowledge of the problem through the use of a intelligent agent, able to recognize promising regions and also identify when they should diversify the direction of the search. This way, this work proposes the use of Reinforcement Learning technique - Q-learning Algorithm - as exploration/exploitation strategy for the metaheuristics GRASP (Greedy Randomized Adaptive Search Procedure) and Genetic Algorithm. The GRASP metaheuristic uses Q-learning instead of the traditional greedy-random algorithm in the construction phase. This replacement has the purpose of improving the quality of the initial solutions that are used in the local search phase of the GRASP, and also provides for the metaheuristic an adaptive memory mechanism that allows the reuse of good previous decisions and also avoids the repetition of bad decisions. In the Genetic Algorithm, the Q-learning algorithm was used to generate an initial population of high fitness, and after a determined number of generations, where the rate of diversity of the population is less than a certain limit L, it also was applied to supply one of the parents to be used in the genetic crossover operator. Another significant change in the hybrid genetic algorithm is the proposal of a mutually interactive cooperation process between the genetic operators and the Q-learning algorithm. In this interactive/cooperative process, the Q-learning algorithm receives an additional update in the matrix of Q-values based on the current best solution of the Genetic Algorithm. The computational experiments presented in this thesis compares the results obtained with the implementation of traditional versions of GRASP metaheuristic and Genetic Algorithm, with those obtained using the proposed hybrid methods. Both algorithms had been applied successfully to the symmetrical Traveling Salesman Problem, which was modeled as a Markov decision process

Aplicaçaõ das técnicas Path-relinking e Vocabulary buiding na melhoria de performance do algoritmo memético para o problema do caixeiro viajante assimétrico

The present essay shows strategies of improvement in a well succeded evolutionary metaheuristic to solve the Asymmetric Traveling Salesman Problem. Such steps consist in a Memetic Algorithm projected mainly to this problem. Basically this improvement applied optimizing techniques known as Path-Relinking and Vocabulary Building. Furthermore, this last one has being used in two different ways, in order to evaluate the effects of the improvement on the evolutionary metaheuristic. These methods were implemented in C++ code and the experiments were done under instances at TSPLIB library, being possible to observe that the procedures purposed reached success on the tests done

Teoria dos grafos e suas aplicações

Pós-graduação em Matemática Universitária - IGCE

A Study of Different Subsequence Elimination Strategies for the Soft Drink Production Planning

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Reformulações para o problema integrado de dimensionamento e sequenciamento da produção

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Large-scale Network Analysis on Distributed Architectures

Questa dissertazione esamina le sfide e i limiti che gli algoritmi di analisi di grafi incontrano in architetture distribuite costituite da personal computer. In particolare, analizza il comportamento dell'algoritmo del PageRank così come implementato in una popolare libreria C++ di analisi di grafi distribuiti, la Parallel Boost Graph Library (Parallel BGL). I risultati qui presentati mostrano che il modello di programmazione parallela Bulk Synchronous Parallel è inadatto all'implementazione efficiente del PageRank su cluster costituiti da personal computer. L'implementazione analizzata ha infatti evidenziato una scalabilità negativa, il tempo di esecuzione dell'algoritmo aumenta linearmente in funzione del numero di processori. Questi risultati sono stati ottenuti lanciando l'algoritmo del PageRank della Parallel BGL su un cluster di 43 PC dual-core con 2GB di RAM l'uno, usando diversi grafi scelti in modo da facilitare l'identificazione delle variabili che influenzano la scalabilità. Grafi rappresentanti modelli diversi hanno dato risultati differenti, mostrando che c'è una relazione tra il coefficiente di clustering e l'inclinazione della retta che rappresenta il tempo in funzione del numero di processori. Ad esempio, i grafi Erdős–Rényi, aventi un basso coefficiente di clustering, hanno rappresentato il caso peggiore nei test del PageRank, mentre i grafi Small-World, aventi un alto coefficiente di clustering, hanno rappresentato il caso migliore. Anche le dimensioni del grafo hanno mostrato un'influenza sul tempo di esecuzione particolarmente interessante. Infatti, si è mostrato che la relazione tra il numero di nodi e il numero di archi determina il tempo totale.

Synchronization and Detection Techniques for Navigation and Communication Systems

Synchronization is a key issue in any communication system, but it becomes fundamental in the navigation systems, which are entirely based on the estimation of the time delay of the signals coming from the satellites. Thus, even if synchronization has been a well known topic for many years, the introduction of new modulations and new physical layer techniques in the modern standards makes the traditional synchronization strategies completely ineffective. For this reason, the design of advanced and innovative techniques for synchronization in modern communication systems, like DVB-SH, DVB-T2, DVB-RCS, WiMAX, LTE, and in the modern navigation system, like Galileo, has been the topic of the activity. Recent years have seen the consolidation of two different trends: the introduction of Orthogonal Frequency Division Multiplexing (OFDM) in the communication systems, and of the Binary Offset Carrier (BOC) modulation in the modern Global Navigation Satellite Systems (GNSS). Thus, a particular attention has been given to the investigation of the synchronization algorithms in these areas.

Design and implementation of a novel multi-constellation FPGA-based dual frequency GNSS receiver for space applications

The PhD activity described in the document is part of the Microsatellite and Microsystem Laboratory of the II Faculty of Engineering, University of Bologna. The main objective is the design and development of a GNSS receiver for the orbit determination of microsatellites in low earth orbit. The development starts from the electronic design and goes up to the implementation of the navigation algorithms, covering all the aspects that are involved in this type of applications. The use of GPS receivers for orbit determination is a consolidated application used in many space missions, but the development of the new GNSS system within few years, such as the European Galileo, the Chinese COMPASS and the Russian modernized GLONASS, proposes new challenges and offers new opportunities to increase the orbit determination performances. The evaluation of improvements coming from the new systems together with the implementation of a receiver that is compatible with at least one of the new systems, are the main activities of the PhD. The activities can be divided in three section: receiver requirements definition and prototype implementation, design and analysis of the GNSS signal tracking algorithms, and design and analysis of the navigation algorithms. The receiver prototype is based on a Virtex FPGA by Xilinx, and includes a PowerPC processor. The architecture follows the software defined radio paradigm, so most of signal processing is performed in software while only what is strictly necessary is done in hardware. The tracking algorithms are implemented as a combination of Phase Locked Loop and Frequency Locked Loop for the carrier, and Delay Locked Loop with variable bandwidth for the code. The navigation algorithm is based on the extended Kalman filter and includes an accurate LEO orbit model.

Verso una teoria delle differenze tra documenti semi-strutturati

I sistemi di versionamento moderni quali "git" o "svn" sono ad oggi basati su svariati algoritmi di analisi delle differenze (detti algoritmi di diffing) tra documenti (detti versioni). Uno degli algoritmi impiegati con maggior successo a tal proposito è il celebre "diff" di Unix. Tale programma è in grado di rilevare le modifiche necessarie da apportare ad un documento al fine di ottenerne un altro in termini di aggiunta o rimozione di linee di testo. L'insieme di tali modifiche prende nome di "delta". La crescente richiesta e applicazione dei documenti semi-strutturati (ed in particolar modo dei documenti XML) da parte della comunità informatica soprattutto in ambito web ha motivato la ricerca di algoritmi di diffing più raffinati che operino al meglio su tale tipologia di documenti. Svariate soluzioni di successo sono state discusse; algoritmi ad alte prestazioni capaci di individuare differenze più sottili della mera aggiunta o rimozione di testo quali il movimento di interi nodi, il loro riordinamento finanche il loro incapsulamento e così via. Tuttavia tali algoritmi mancano di versatilità. L'incapsulamento di un nodo potrebbe essere considerata una differenza troppo (o troppo poco) generale o granulare in taluni contesti. Nella realtà quotidiana ogni settore, pubblico o commerciale, interessato a rilevare differenze tra documenti ha interesse nell'individuarne sempre e soltanto un sottoinsieme molto specifico. Si pensi al parlamento italiano interessato all'analisi comparativa di documenti legislativi piuttosto che ad un ospedale interessato alla diagnostica relativa alla storia clinica di un paziente. Il presente elaborato di tesi dimostra come sia possibile sviluppare un algoritmo in grado di rilevare le differenze tra due documenti semi-strutturati (in termini del più breve numero di modifiche necessarie per trasformare l'uno nell'altro) che sia parametrizzato relativamente alle funzioni di trasformazione operanti su tali documenti. Vengono discusse le definizioni essenziali ed i principali risultati alla base della teoria delle differenze e viene dimostrato come assunzioni più blande inducano la non calcolabilità dell'algoritmo di diffing in questione.