Lidar-aided Autonomous Landing and Vision-based Taxiing for Fixed-Wing UAV

Autonomous UAV technology is limited in its ability to land safely at distinct airfields that have not been precisely surveyed and where GPS is unavailable. In this paper, we present a multi-sensor system for the automatic landing of fixed-wing UAV. The system is composed of a high precision aircraft controller, a range finder (Lidar) and a vision module used for detection and tracking of runways. The estimation of the position of the fixed-wing UAV is by using Lidar and performs gliding till flaring. Then, a federated extended Kalman filter (EKF) structure is costumed and utilizes the solutions of the IMU, GPS and Lidar as independent measurements to estimate the position of the vehicle. The framework can be used to integrate the vision solutions and enables the estimation to be smooth and robust landing. For taxiing, the neural network is used such that from live video stream from the camera trains the UAV to land precisely along the runway.