Probabilistic localization by appearance models and active vision

In order to do useful things a mobile robot needs some sort of global information about the environment it is operating in. In the 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 use computer vision. The model gives a probability distribution over the learned locations given an observation. We developed an active vision strategy to increase the performance and tested the method on real image data from our robot