Vision based automatic control and target tracking of a quadcopter

In this study, motion of a quadcopter (that is called DRIHA) to track a target is auto controlled based on the data acquired by images. The images are taken by the monocular camera mounted on the center of gravity of the DRIHA. The detected target is automatically tracked by proposed methods. Designed controllers control translational and rotational motion with respect to the motion occurred in images. An image error vector is proposed to reduce the effects of error signals on the motion. Controllers are designed for controlling the pitch, roll, and yaw angles using the features in the image plane. The model developed by the image-based visual servoing (IBVS) approach is tested in the Gazebo simulation environment. Simulation test results validate effectiveness of the proposed system that includes simultaneous and comprehensive designs in terms of automatic control and target tracking performance. The proposed methods enable autonomous navigation applications even in environments where global positioning systems are unavailable