Obstacle Detection and Collision Avoidance of Quadrotor UAV Using Depth Map of Stereo Vision
Jongho Park, Youdan Kim · AIAA Guidance, Navigation, and Control (GNC) Conference · 2013
Collision avoidance scheme of a quadrotor unmanned aerial vehicle using stereo vision sensor is proposed. Mathematical model of the quadrotor is performed, and under-actuated problem of the quadrotor is treated by introducing virtual inputs. Stereo vision is used to obtain depth map information, which is utilized to detect an obstacle. Collision cone approach is adopted to avoid collision between the quadrotor and the detected obstacle. Probability of the collision is computed by utilizing the relationship between the velocity vector of the quadrotor and the collision cone. The location and size information of the detected obstacles are accumulated to build the circumscribed spheres of the obstacles, which are used to eliminate a possibility of collision when the stereo vision does not detect any obstacle in the depth map of the current image. Multiple obstacles are also dealt by creating clusters in the image plane. Waypoint guidance and control system is designed using feedback linearization and linear quadratic tracker. Finally, numerical simulations are performed to validate the performance of the proposed collision avoidance scheme.