This paper aims to investigate a vision-based integrated navigation system using an optical flow vector, which is able to operate in GPS-denied environments. The system consists of GPS, IMU, magnetometer and dual vision sensors for measuring forward and downward optical flow vectors. In this system, hybrid optical flow method is adopted to reduce the computational burden. Using this measurement, INS/Vision integrated navigation filter is constructed based on the Kalman filter approach. Feasibility of the navigation filter is proven via simulation results of three dimensional trajectory. Finally, with the developed real-time hardware prototype, an indoor test is carried out for analyzing real-time navigation performance of the proposed system.
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