This paper presents a vision-based methodology which makes use of a stereo\ncamera rig and a one dimension LiDAR to estimate free obstacle areas for\nquadrotor navigation. The presented approach fuses information provided by a\ndepth map from a stereo camera rig, and the sensing distance of the 1D-LiDAR.\nOnce the depth map is filtered with a Weighted Least Squares filter (WLS), the\ninformation is fused through a Kalman filter algorithm. To determine if there\nis a free space large enough for the quadrotor to pass through, our approach\nmarks an area inside the disparity map by using the Kalman Filter output\ninformation. The whole process is implemented in an embedded computer Jetson\nTX2 and coded in the Robotic Operating System (ROS). Experiments demonstrate\nthe effectiveness of our approach.\n