Simultaneous Localization and Map Building Algorithm for Real-Time Applications

Mobile robot navigation in unstructured environment is a challenging task due to the uncertain nature of the real world. Navigating using visual landmarks could be a mandatory skill together with the ability of building a representation of the world around the robot. This mapping aptitude should be implemented as an efficient real-time task, even if a large number of elements have to be included in the map itself. To this aim, and to help in localising the robot, a promising technique is given by the Extended Kalman Filter in its interlaced version. The resulting SLAM algorithm, proposed in this paper, has a reduced computational cost preserving, at the same time, a good performance.