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In this paper a stereo vision-based algorithm for mobile robots navigation and exploration in unknown outdoor environments is proposed. The algorithm is solely based on stereo images and implemented on a nonholonomic mobile robot. The first step for exploration in unknown environments is construction of the map of circumference in real-time. By getting disparity image from rectified stereo images and translating its data to 3D-space, point cloud model of environments is constructed. Then by projecting points to XZ plane and put local maps together based on visual odometry, global map of environment is constructed in real-time. A* algorithm is used for investigating optimal path and nonlinear back-stepping controller guides the robot to follow the identified path. Finally, the mobile robot explores for a desired object in an unknown environment through these steps. Experimental results verify the effectiveness of the proposed algorithm in real-time implementations.