Vision Based Obstacle Detection and Avoidance for UAVs Using Image Segmentation
Pooja Agrawal, Ashwini Ratnoo, Debasish Ghose · 2015
The present work proposes a vision based guidance scheme for an unmanned aerial vehicle (UAV) navigating through urban environments. Optical flow of image feature is considered to segment obstacles from the image. With the segmented obstacles, a collision cone based guidance law is proposed for avoidance. Detecting open space between segmented obstacles, a passage following guidance law is also presented for intelligent decision making. Simulations are carried out in a 3D environments created in VRML toolbox of MATLAB R ©. Results shows a much improved performance as compared to existing optical flow based obstacle avoidance methods.