Consistent on line estimation of environment features aimed at enhancing the efficiency of the localization procedure for a powered wheelchair

A basic requirement for an autonomous mobile robot is to localize itself with respect to a given coordinate system. The relative methods and algorithms are strongly influenced by the a priori knowledge on the environment where the robot operates. If the environment is only partially known the localization algorithm needs a preliminary definition of a suitable environment map. In this paper the localization and environment features estimation problems are formulated in a stochastic setting and a Kalman filtering approach is proposed for the integration of odometric, gyroscope and sonar measures