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In this study, we focus on the problem of landing an unmanned aerial vehicle (UAV) in unknown and Global Navigation Satellite System(GNSS)-denied environments based on an infrared stereo vision system. This system is fixed on the ground and used to track the UAV's position during the landing process. In order to enlarge the search field of view (FOV), a pan-tilt unit (PTU) is employed to actuate the vision system. The infrared camera is chosen as the exteroceptive sensor for two main reasons: first, it can be used under all weather conditions and around the clock; second, infrared targets can be tracked based on infrared spectrum features at a lower computational cost compared to tracking texture features in visible spectrum. State-of-the-art active contour based algorithms and the mean shift algorithm have been evaluated with regard to detecting and tracking an infrared target. Field experiments have been carried out using an unmanned quadrotor and a fixed-wing unmanned aircraft, with both qualitative and quantitative evaluations. The results demonstrate that our system can track UAVs without artificial markers and is sufficient to enhance or replace the GNSS-based localization in GNSS-denied environment or where its information is inaccurate.
Kong et al. (Fri,) studied this question.