Vitor Greati

Unmanned aerial vehicles have shown to be very useful in different applications aimed at facil- itating and speeding up tasks on the civil context. Among them, one can mention commercial delivery as a strong application for the future, especially after promising initiatives from large companies, such as Amazon. However, the difficulty in precisely defining landing points is one of the factors that prevent the execution of these ideas. This paper presents a new visual approach to UAV autonomous landing by introducing a visual tag positioned over a helipad, composed by a color pattern in HSV space, and an algorithm responsible for providing the precise landing position to the control system, based on the images captured by a camera coupled to the UAV. These images are first filtered by a fuzzy classifier in order to eliminate pixels incompatible to the searched pattern. Then, the remaining pixels are grouped by color and proximity, creating clusters that, when considered as groups, may represent the searched tag. Finally, the algorithm calculates the center of the helipad relative to the vehicle. Experiments were performed with very limited hardware and have demonstrated that the solution is effective and quick enough for real time applications.