  This paper presents a vision-based methodology which makes use of a stereo
camera rig and a one dimension LiDAR to estimate free obstacle areas for
quadrotor navigation. The presented approach fuses information provided by a
depth map from a stereo camera rig, and the sensing distance of the 1D-LiDAR.
Once the depth map is filtered with a Weighted Least Squares filter (WLS), the
information is fused through a Kalman filter algorithm. To determine if there
is a free space large enough for the quadrotor to pass through, our approach
marks an area inside the disparity map by using the Kalman Filter output
information. The whole process is implemented in an embedded computer Jetson
TX2 and coded in the Robotic Operating System (ROS). Experiments demonstrate
the effectiveness of our approach.
