Autonomous Quadrotor Navigation With Vision Based Obstacle Avoidance and Path Planning

Due to the high demands on military and commercial applications, the development of UAVs (unmanned aerial vehicles) has become increasingly important in recent years. In this paper, we present a vision guided autonomous navigation approach for quadrotor UAVs. A map-based offline path planning technique is developed to generate an initial path, followed by the waypoints of the trajectory for flight guidance. During the navigation, an onboard camera is utilized to acquire a sequence of monocular images for environment perception. A vision-based obstacle detection technique using optical flow is proposed for collision avoidance. The optical flow field constructed from the image sequence is used to provide the depth cues for the incoming obstacle detection. A single-board computer is adopted as a control platform, and the proposed algorithms are implemented for online and real-time processing. Several experiments are carried out in the outdoor environment for obstacles avoidance and visual guidance. The results have demonstrated the feasibility of our proposed method for path planning and autonomous navigation.