Improved Vision-Based Algorithm for Unmanned Aerial Vehicles Autonomous Landing

Abstract

In vision-based autonomous landing system of UAV (Unmanned Aerial Vehicle), the efficiency of object detection and tracking will directly affect the control system. An improved algorithm of SURF (Speed Up Robust Features) will resolve the problem which is inefficiency of the SURF algorithm in the autonomous landing system of UAV. The improved algorithm is composed of three steps: first, detect the region of the target using the Camshift (Continuously Adaptive Mean-SHIFT) algorithm; second, detect feature points in the region of the above acquired using the SURF algorithm; third, do the matching between the template target and the region of target in frame. Results of experiments and theoretical analysis testify the efficiency of the algorithm. We also show the experiments that demonstrate that the UAV can autonomous land without using GPS, or without specific assumptions about the environment.