An efficient navigation strategy for mobile robots with uncertainty estimation

The main contribution of this paper is an algorithm for integrating motion planning and simultaneous localization and mapping (SLAM). We propose an effective navigation method and take into account not only the specific exploration situation, but also the uncertainty estimation of localization and mapping. In our method, both the navigation cost and the system uncertainty constitute an objective function. The robot will plan an optimal path based on this function between its current location and a selected local destination in order to implement the whole navigation process in an active and intelligent way. Simulation results are given for confirmation and it is shown that our method is a success in unknown corridor-like environment as it leads to more accurate localization and mapping result compared with the traditional method.