LVIO-based map generation and pose estimation of an unmanned drone using a monocular camera for an indoor flight

For autonomous flight of drone, pose estimation is required. Especially, in case of indoor flight, the importance of pose estimation is increased. Because when the drone is flying indoors, GPS is not received and there are many obstacles around. In this paper, we propose a precise pose estimation method through LVIO (Lidar Visual Inertial Odometry) algorithm using IMU, vision sensor and LIDAR. In addition, we generate a 3D feature point map and used the pre-generated map and monocular camera to perform pose estimation for indoor flight of a small drones. Generally, the indoor environment is mostly narrow, we can use only small size drone for indoor flight. Therefore, we can only mount light sensors on the drone for pose estimation such as monocular camera and IMU. Therefore, in this paper, LVIO is used to generate the precise trajectory when generating the map, and the pose is estimated using only pre-generated map and monocular camera for drone flight. In addition, it is confirmed that precise pose estimation result is obtained by using LVIO through experiment, and pose estimation for indoor flight is performed using only map and monocular camera. © ICROS 2019.