In order to do useful things a mobile robot needs some sort of global information about the environment it is operating in. In this paper an approach is described where the global information is not cast in a model of the geometry of the environment but in a model of all sensory data of the robot. As a primary sensing system we used computer vision. The model gives a probability distribution ov...

This report describes the robot, Curious George, that took part in, and won, the robot league of the 2007 Semantic Robot Vision Challenge (SRVC), held at the AAAI’07 conference in Vancouver, Canada. We describe the robot hardware, the algorithms used during each of the three competition phases, as well as the results obtained by the system during the competition.

Plenoptic models, representatives are the lightfield or the lumigraph, have been successfully applied in computer vision and computer graphics in the past five years. The key idea is to model objects and scenes using images and some extra information like camera parameters or coarse geometry. The model differs from CAD–models in the photorealism that can be achieved and is thus superior in appl...

The key component of a mobile robot system is the ability to localize itself accurately in an unknown environment and simultaneously build the map of the environment. Majority of the existing navigation systems are based on laser range finders, sonar sensors or artificial landmarks. Navigation systems using stereo vision are rapidly developing technique in the field of autonomous mobile robots....