World Modelling and Sensor Data Fusion in a Non Static Environment. Application to Mobile Robots

Abstract We describe a world modelling method able to integrate static and moving objects existent in dynamic environments. The static world is modelled by using an occupancy grid. The method is capable of modelling several moving objects. Whereas measurements belonging to actual targets are processed using a Kalman filter to yield optimum estimates, all other measurements are used to create or maintain multiple hypothesis corresponding to possible mobile objects. The viability of the method has been tested in a real mobile robot. Portions of this research has been performed under the EEC ESPRIT 2483 Panorama Project.