Visual aid for unmanned aircraft navigation in unknown environments

Abstract

This study presents a visual-aided inertial navigation technique that can be used for unmanned aircraft in unknown environments. An angular and linear velocity estimation algorithm, which is based on the solution of the Wahba’s problem, is developed using sequential images for visual odometry. It is possible that the visual sensors do not receive continuous measurements throughout the mission, for example, when a sufficient number of features cannot be detected by the camera. Considering that a closed loop Extended Kalman Filter algorithm is designed for integration of visual odometry measurements with the inertial measurements to have accurate pose estimation throughout the flight.