Omnidirectional Vision Based Topological Navigation

Goedemé T., Van Gool L., ''Omnidirectional vision based topological navigation'', Mobile robots navigation, pp. 172-196, Barrera Alejandra, ed., March 2010, InTech.status: publishe

Robot coordination to create collaborative panorama images

In this work, we deal with the problem of coordinating a set of autonomous agents equipped with cameras whose goal is to obtain a panoramic image. To this end, we optimize a multiple-objective cost function that accounts for the number of matched points between the images, the distance between the agents or the distance from the visual central point. Some solutions for this problem are presented considering two di erent approaches: centralized and distributed coordination of the agents. For each one of them, the results are obtained using optimization methods and heuristic methods. The comparisons between all of them are done from the simulations of the algorithms developed.En este proyecto se trata el problema de la coordinaci on de un conjunto de agentes aut onomos, cada uno de ellos equipado con una c amaras, cuyo objetivo es la obtenci on de una imagen panor amica. Para este n, se optimiza una funci on objetivo de costes m ultiples que representa, por ejemplo, el n umero de puntos emparejados entre las im agenes, la distancia entre los agentes o la distancia hasta el punto central de visi on. Se presentan algunas soluciones para de problema bas andonos en dos enfoques diferentes: las coordinaciones centralizada y distribuida de los agentes. Para cada uno de ellos, los resultados se obtienen utilizando tanto m etodos de optimizaci on como m etodos heur sticos. Las comparaciones entre todos los resultados obtenidos se realizan a partir de las simulaciones de los algoritmos que se desarrollan durante este proyecto.Universidad de Sevilla. Grado en Ingeniería de Tecnologías Industriale

Learning cognitive maps: Finding useful structure in an uncertain world

In this chapter we will describe the central mechanisms that influence how people learn about large-scale space. We will focus particularly on how these mechanisms enable people to effectively cope with both the uncertainty inherent in a constantly changing world and also with the high information content of natural environments. The major lessons are that humans get by with a less is more approach to building structure, and that they are able to quickly adapt to environmental changes thanks to a range of general purpose mechanisms. By looking at abstract principles, instead of concrete implementation details, it is shown that the study of human learning can provide valuable lessons for robotics. Finally, these issues are discussed in the context of an implementation on a mobile robot. © 2007 Springer-Verlag Berlin Heidelberg