This paper describes the efficient strategy for planning for autonomous mobile robot navigation using the information which is the resulting probabilistic distribution of position and map acquired by solving the SLAM. In order to estimate good robots position and map, we used a highly efficient variant of the grid based version of the FastSLAM algorithm. D* Lite algorithm for global path planning, which has the effective replanning at the partial cost field changed, was employed. Because the acquired map in the SLAM is also grid based which indicates the probabilistic existence of the obstacles in each grid, and SLAMs uncertain grid map is utilized to compute the cost field for path planning. In this research, it was proven that the mobile robot could carry out autonomous navigation in the outdoor field without prior information. This paper presented that the mobile robot reached the predefined goal with estimating good position and map simultaneously.