Quadcopter localization and health monitoring method based on multiple virtual silhouette sensor integration

With the widespread deployment of quadcopters, the flight safety issue attracts increasingly public and academic attentions. This article presents a quadcopter flight regime extraction algorithm for quadcopter localization and health monitoring using imageries captured by general purpose monocular cameras. First, contour information is extracted from quadcopter shadows on the ground. In order to better illustrate the three-dimensional silhouette information contained in shadow contour on the ground, a virtual sensor named Shadow Projection Tunnel is designed. Then, multiple Shadow Projection Tunnels are generated according to the extracted silhouette information and corresponding light source positions. Finally, three-dimensional quadcopter positions and flight regimes are extracted based on the aggregation between multiple Shadow Projection Tunnels. The proposed method is validated to be accurate and efficient in monitoring quadcopter position and flight regimes based on the comparative analyses. In comparison with traditional quadcopter health monitoring methods, the proposed method has advantages on deployment convenience, system robustness, precision expandability, and scenario adaptability, making it an ideal solution for quadcopter monitoring in outdoor scenarios.