Novel Autonomous Navigation Algorithms in Dynamic and Unknown Environments

Because the range of mobile robot sensors is limited and navigation maps are not always accurate, autonomous navigation in dynamic and unknown environments is a big challenge. In this article, we propose two novel autonomous navigation algorithms, which are based on the analysis of three conditions for unobserved and uncertain environments during navigation. The algorithm for a dynamic environment uses the “known space” and “free space” conditions. It corrects false obstacles in the map when the conventional path is stuck. The navigation algorithm for unknown environments uses the “unknown space” and “free space” conditions. We use the 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.