Skip to Main Content
We propose a new localization and map building method similar to that of human being in the navigation problem. Human being is assumed to solve a problem through four processes: exploration process (EP), decision process (DP), behavior process (BP) and learning process (LP). We call the processes as human being's capability for solving problems. In this paper, we try to solve navigation problems by transferring this human being's capability into a mobile robot. Firstly, in the exploration process, the mobile robot collects the environment information and builds the map using the method called 'graph'. Secondly, in the decision process, the mobile robot selects a proper action on the basis of the percepted information and the generated 'graph'. Thirdly, in the behavior process, the selected action is implemented in accordance with the output of the FIS (fuzzy inference system). Finally, in the learning process, the parameters of 'graph' are updated via repeated implementing. We show that this method is promising for the mobile navigation problems through a number of simulations.