Abstract
Recently, application of Unmanned Aerial Vehicle (UAV) attract much attention of not only academic but also industrial community. To control and make the most of UAV, state estimation is mandatory and it should work accurately on Real-time on computational-limited onboard PC. Especially, for the cases that GNSS-disabled environments or indoor situation, Visual Inertial Odometry using camera and IMU sensor has been actively studied. Generally, to research and develop the indoor navigation algorithm, high-performanced and super-expensive facilities like motion capture cameras are needed to measure the ground-truth. In this paper, we apply state-of-art Visual Inertial Odometry algorithms for state estimation of UAVs to FlightGoggles simulator which is photorealistic and which reflects UAV's real dynamics. Moreover, we compare the performance and resource utilization of those algorithms.
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