Towards autonomous landing on a moving vessel through fiducial markers

This paper propose an autonomous landing method for unmanned aerial vehicles (UAVs), aiming to address those situations in which the landing pad is the deck of a ship. Fiducial marker are used to obtain the six-degrees of freedom (DOF) relative-pose of the UAV to the landing pad. In order to compensate interruptions of the video stream, an extended Kalman filter (EKF) is used to estimate the ship's current position with reference to its last known one, just using the odometry and the inertial data. Due to the difficulty of testing the proposed algorithm in the real world, synthetic simulations have been performed on a robotic test-bed comprising the AR Drone 2.0 and the Husky A200. The results show the EKF performs well enough in providing accurate information to direct the UAV in proximity of the other vehicle such that the marker becomes visible again. Due to the use of inertial measurements only in the data fusion process, this solution can be adopted in indoor navigation scenarios, when a global positioning system is not available.