Autonomous quadrotor flight with vision-based obstacle avoidance in virtual environment

In this paper, vision-based autonomous flight with a quadrotor type unmanned aerial vehicle (UAV) is presented. Automatic detection of obstacles and junctions are achieved by the use of optical flow velocities. Variation in the optical flow is used to determine the reference yaw angle. Path to be followed is generated autonomously and the path following process is achieved via a PID controller operating as the low level control scheme. Proposed method is tested in the Google Earth(R) virtual environment for four different destination points. In each case, autonomous UAV flight is successfully simulated without observing collisions. The results show that the proposed method is a powerful candidate for vision based navigation in an urban environment. Claims are justified with a set of experiments and it is concluded that proper thresholding of the variance of the gradient of optical flow difference have a critical effect on the detectability of roads having different widths.