A Vision-Based Approach for Unmanned Aerial Vehicle Landing

In this paper we present an on-board Computer Vision System for the pose estimation of an Unmanned Aerial Vehicle (UAV) with respect to a human-made landing target. The proposed methodology is based on a coarse-to-fine approach to search the target marks starting from the recognition of the characteristics visible from long distances, up to the inner details when short distances require high precisions for the final landing phase. A sequence of steps, based on a Point-to-Line Distance method, analyzes the contour information and allows the recognition of the target also in cluttered scenarios. The proposed approach enables to fully assist the UAV during its take-off and landing on the target, as it is able to detect anomalous situations, such as the loss of the target from the image field of view, and the precise evaluation of the drone attitude when only a part of the target remains visible in the image plane. Several indoor and outdoor experiments have been carried out to demonstrate the effectiveness, robustness and accuracy of developed algorithm. The outcomes have proven that our methodology outperforms the current state of art, providing high accuracies in estimating the position and the orientation of landing target with respect to the UAV.