It goes without saying that in such a sophisticated world the prominent role of the robots cannot be eliminated. When it comes to the Robots, controversy surrounds the issue how to construct an autonomous robot. The aim of this thesis is the indoor autonomous flight and exploration of a Quad-Rotor robot by a monocular SLAM. In general, this study consists of two parts, namely estimating the 3D robot position and reconstructing the environment map, and determining the unseen areas and generating an appropriate path to explore such areas. The former part encompasses some methods for scale correction, information filtering, and map enrichment. To estimate the robot position and reconstruct the environment map in this thesis ORB-SLAM 2 has been used which works based on detecting corner features of image sequence and preduces sparse map. Morover, filtering and linear fiiting methods have been utilized for the sake of scaling factor correction and data compensation as well the new method has been presented for map enrichment. The latter part consists of unexplored area detection, goal determination, and path generation parts. The suitable and new method has been proposed for distinguishing the accessible and unaccessible localities and obstacles for exploring the environments as far as possible. Furthurmore, the new aproch for generating appropriate path has been proposed which includes some various path planning methods. All of the presented algorithms have been implemented using low cost commercial Quad-Rotor called AR.Drone and in the Robot Operating System (ROS). Moreover, experimental verifications of the proposed algorithms are reported.