In this work, we suggest a novel solution to a very specific problem—calculating the pose (position and attitude) of a micro-aerial vehicle (MAV) operating inside corridors and in front of windows. The proposed method makes use of a single image captured by a front facing camera, of specific features whose three-dimensional (3D) model is partially known. No prior knowledge regarding the size of the corridor or the window is needed, nor is the ratio between their width and height. The position is calculated up to an unknown scale using a gain scheduled iterative algorithm. In order to compensate for the unknown scale, an adaptive controller that ensures consistent closed loop behavior is suggested. The attitude calculation can be used as is, or the results can be fused with angular velocity sensors to achieve better estimation. In this paper, the algorithm is presented and the approach is demonstrated with simulations and experiments.
Adaptive Visual Servoing for Obstacle Avoidance of Micro Unmanned Aerial Vehicle with Optical Flow and Switched System Model