A visual protocol for autonomous landing of unmanned aerial vehicles based on fuzzy matching and evolving clustering

This paper proposes a visual approach based on a RGB/HSV tag to precise and autonomous landing of unmanned aerial vehicles (UAV). The proposed tag is correctly identified by an algorithm divided in four stages: hue filtering, clustering, matching and center location. The first stage is based on fuzzy matching and highlights the pixels with similar colors to the searched pattern, while ignores the pixels with different colors. The clustering stage is responsible for grouping the pixels by color and proximity. The matching stage compares the searched and found landing points. Finally, the last stage locates the center of the landing point in relation to the UAV location. The proposed approach is significantly different from the state-of-the art techniques, since it is able not only to correctly identify a designated landing point, but also to distinguish it from different landing points. It requires very low computational effort and is very suitable for real-time video applications. The algorithm was successfully used, in an online manner, for location of landing points in real-time, using very limited hardware.