Appearance based self localization and navigation using place memory

This thesis is concerned with appearance based self-localization and navigation. First, we assume a place-aware robot. Such a robot can recognize a place (i.e. a particular room etc.) after having learned it based on a collection of appearances. A novel approach to self-localization is presented in this framework. In this approach, all the respective learned appearances contribute simultaneously to the location estimation - assuming them to be tagged with their respective locations during learning. With the extensive set of experiments, it is shown that the proposed approach can be used as a solution to mobile robot self-localization. Secondly, we introduce a novel approach in which the robot couples place awareness and self-localization. The robot first recognizes the place and then uses the retrieved appearances from its place memory. Experimental results demonstrate the advantages of coupling place awareness and self-localization. Lastly, the proposed approach is considered in appearance-based navigation.