A new landmark framework for mobile robot localization and asynchronous sensor fusion

This paper presents a new landmark framework for mobile robot localization in which we use a combination of obstacle vertical edge and its corresponding plane angle, that appear in practically all indoor environments, to realize mobile robot localization. Sensor data is assumed to be provided in the form of a Gaussian distribution over the space of the robot poses. We propose a new fusion strategy asynchronous sensor fusion (ASF), which either creates complementaries or adds more redundancy for asynchronous sensor data set will also be presented in this paper. This strategy, combined with dead reckoning, enables mobile robots to asynchronously utilize incomplete information captured by range sensors to localize themselves and simultaneously accomplish map building in a partially known indoor environment.