Abstract
It is an important criterion for unmanned aerial vehicles (UAVs) to land on the runway safely. This paper concentrates on stereo vision localization of a fixed-wing UAV's autonomous landing within global navigation satellite system (GNSS) denied environments. A ground stereo vision guidance system imitating the human visual system (HVS) is presented for the autonomous landing of fixed-wing UAVs. A saliency-inspired algorithm is presented and developed to detect flying UAV targets in captured sequential images. Furthermore, an extended Kalman filter (EKF) based state estimation is employed to reduce localization errors caused by measurement errors of object detection and pan-tilt unit (PTU) attitudes. Finally, stereo-vision-dataset-based experiments are conducted to verify the effectiveness of the proposed visual detection method and error correction algorithm. The compared results between the visual guidance approach and differential GPS-based approach indicate that the stereo vision system and detection method can achieve the better guiding effect.
Highlights
With successful application in many areas, unmanned aerial vehicles (UAVs) have been a popular research topic in the field of robotic systems
Most traditional landing control methods are based around radio waves and the global navigation satellite system (GNSS)
To address the issues noted above, this paper proposes and develops a saliency detection method combined with a filtering correction
Summary
With successful application in many areas, unmanned aerial vehicles (UAVs) have been a popular research topic in the field of robotic systems. The UAV landing process is mainly remote controlled by experienced operators in environments where there is electromagnetic interference In this eye-in-loop process, operators estimate UAV flight states using the human visual system (HVS). Even if the flying vehicle is automatically detected, measurement error still affects localization and guiding accuracy. This inaccuracy is noteworthy in long-distance scenarios. Under such circumstances, the ground stereo system captures sequential images of the flying vehicle. Algorithms of target detection and localization are developed to obtain spatial coordinates for the landing of the aerial vehicle.
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