Hybrid architecture for simultaneous localization and map building in large outdoor areas

This paper address the problem of navigating in very large outdoor unstructured environments. It presents solutions to the problem of closing large loops in simultaneous localization and map building applications. A hybrid architecture is presented that make use of the extended Kalman filter to perform SLAM in an efficient form and a Monte Carlo type filter to resolve the data association problem present when closing large loops. The proposed algorithm incorporates integrity to the standard SLAM algorithms by allowing multimode distribution to be handled in real time. Experimental results in outdoor environments are also presented.