Robust Marker Tracking Algorithm for Precise UAV Vision-based Autonomous Landing

Abstract

The robust marker tracking and relative navigation algorithms are presented for precise UAV vision-based autonomous landing. To recognize the marker in close-range, the concentric circles are adopted as the marker with ellipse fitting algorithm based on Direct Least Square. We assume that IMU provides vehicle's attitude and altitude so that we consider GPS-denied situation. Also multiple ellipses are used to estimate its center pixel coordinate makes UAV land more accurately. To verify the vision-based relative navigation algorithm we suggest, numerical simulations are obtained by using virtual reality toolbox in MATLAB™. We predetermine the true position and attitude of UAV, and the result of the relative position calculated from vision software including the filter is compared. The simulation results show that the algorithm is robust and very accurate.