Towards automated map updating for mobile robot localization

Abstract

In mobile robotics, in order to accomplish a task, self-localization is of paramount importance. It is generally granted that robot localization evolving in an outdoor environment needs an absolute localization technique, which can be map-based. While most of map-based techniques use a static map of the environment, we propose here to handle a dynamic map, which could originate from publicly available Geographical Information Systems (GIS) in which imprecise mapped landmarks would have their own localization updated, unobservable mapped landmarks would be deleted and newly observable landmarks would be added. In this article, our contribution is to demonstrate the possibility to delete dynamically repositionable landmarks in a dynamic environment map on a real vehicle online in real-time, using a partially separated vehicle localization integrity and landmark existence probabilities, based on a Bayesian graphical network formalism.