Object recognition has been widely researched for several decades and in the recent years new methods capable of general object classification have appeared. However very few work has been done to adapt these methods to the challenges raised by mobile robotics. In this article we discuss the data sources (appearence information, temporal context, etc.) that such methods could use and we review several state of the art object recognition methods that build in one or more of these sources. Finally we run an object based robot localization experiment using an state of the art object recognition method and we show that good results are obtained even with a naïve place descriptor.