No abstract

Wireless Sensor Networks (WSN) is a technology that have gained a lot of importance in the last few years. From all the possible applications for WSN, target tracking is considered essential. In this application, the WSN has to determine, in a collaborative way, the trajectory of one or more targets that are within the sensing area of the network.The aim of this document is to present a collaborative algorithm based on multifrontal QR factorization for the solution of the target trajectory estimation problem with WSN. This algorithm uses a batch estimation approach, which assumes that all sensing data are available before the estimation of the target trajectory. If all the observations of the target trajectory is available, the problem can be modeled as an overdetermined system of equations Ax = b where A is sparse. This system of equations is solved by least squares method. The multifrontal QR factorization uses a tree graph called elimination tree to reorganize the overall factorization of a sparse matrix into a sequence of partial factorizations of dense smaller matrices named frontal matrices. By mapping the elimination tree into the WSN, the sensor nodes that observed the target can factorize the frontal matrices. In this manner, the WSN factorizes the matrix A in a collaborative way, dividing the work in small tasks that the sensor nodes could execute.

RESUMOEste trabalho apresenta o desenvolvimento dos algoritmos de controle de um robô móvel autônomo para coleta de lixo. O objetivo do robô é coletar latas de refrigerante espalhadas pelo chão. O sistema de navegação do robô foi implementado utilizando a arquitetura denominada "Motor-Schema". Essa arquitetura fornece um método para projetar comportamentos primitivos que atuam em forma paralela para realizar ações robóticas inteligentes em resposta aos estímulos do ambiente. O sistema de controle apresentado foi constituído por vários comportamentos primitivos que, coordenados, permitiram ao robô explorar de forma segura um ambiente desconhecido, detectar e coletar o lixo e levá-lo num depósito determinado. Os algoritmos desenvolvidos foram testados utilizando uma ferramenta de simulação 2D denominada Player/Stage. Os resultados obtidos mostraram que a solução apresentada é adequada para resolver a aplicação robótica de coleta de lixo. ABSTRACTThis work presents the control system for an autonomous mobile robot for soda can collection. The navigation system is implemented using a reactive architecture called "Motor-Schema". This architecture provides a methodology to design primitive behaviors that can act in a distributed and parallel manner to yield intelligent robotic actions in response to environmental stimuli. The control system is composed of several primitive behaviors, which enable the robot explore an unknown environment, detect and collect the soda cans and navigate toward a soda can reservoir. The algorithms are tested using Player/Stage, a software for 2D simulation. The results show that the solution is suitable for soda can collection.