Trejo, Sergio Marcelino (Centro de Investigaciones en Optica), Martínez, Karla (Centro de Investigaciones en Óptica), Flores, Gerardo (Center for Research in Optics)

Depth Map Estimation Methodology for Detecting Free-Obstacle Navigation Areas

Scheduled for presentation during the Regular Session "Sensor Fusion I" (ThB3), Thursday, June 13, 2019, 15:10−15:30, Heritage A

2020 International Conference on Unmanned Aircraft Systems (ICUAS), June 11-14, 2019, Athens, Greece

This information is tentative and subject to change. Compiled on April 18, 2024

Abstract

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 a 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 demonstrates the effectiveness of our approach.