Vision-Based Pose Estimation for Autonomous Outdoor Navigation of Aerial Vehicles

During the development of Unmanned Aerial Vehicles (UAVs), one of the major concerns has been the issue of improving the accuracy, coverage, and reliability of automatic navigation systems within the imposed weight and cost limitations. Standard aerial navigation systems often rely on Global Positioning System (GPS) and Inertial Measurement Unit (IMU), alone or in combination. In aerial vehicles the GPS signal can becomes unreliable, blocked or jammed (especially for a GPS operating on civilian frequencies). On the other hand, the stand-alone IMU drifts with time and will be unacceptable after a few seconds (especially for small-size aerial vehicles which use low-cost IMU). In order to overcome the disadvantages of both GPS and IMU, many researchers have been proposed the visionaided navigation system which helps estimating pose of the aerial vehicles. This paper represents a method for visionbased navigation of aerial vehicles which is to determine precise pose parameters of the vehicle in real time. The pose estimation strategy has been tested on a number of different images and experimental results prove the feasibility and robustness of the method.