Novel autonomous navigation algorithms in dynamic and unknown environments

Because the range of mobile robot sensor is limited and the navigation map is not accurate, autonomous navigation in dynamic and unknown environment is a big challenge. In this paper, we propose two novel autonomous navigation algorithms, which are based on the analysis of three conditions for unobserved and uncertainty environment during the navigation. The algorithm for dynamic environment uses the "known space" and "free space" conditions. It corrects false obstacles in the map when conventional path is stuck. The navigation algorithm for unknown environment uses the "unknown space" and "free space" conditions. We use Monte Carlo method to evaluate the performance of our algorithms and the other methods. Experimental results show that our autonomous navigation algorithms are better than the others.