Integrated vision/inertial navigation method of UAVs in indoor environment
WANG Tingting1, CAI Zhihao1,2, WANG Yingxun1,2
1. School of Automation Science and Electrical Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100083, China;
2. Aircraft Control Integration National Defense Key Laboratory, Beijing University of Aeronautics and Astronautics, Beijing 100083, China
Abstract：A new integrated navigation method based on inertial sensor,optical flow and visual odometry is proposed for self-navigation indoor in GPS-denied environment. An ORB optical flow based method is also proposed for estimating real-time three-axis velocity of the UAV. The algorithm improves the traditional pyramid Lucas-Kanade method using sparse optical flow based on feature points. The tracking of feature points is made more accurate by applying forward-backward tracking and random sampling consensus strategies. For position estimation, a visual odometry method with integrated vision/inertial navigation is adopted, which uses the artificial icon method, visual optical flow information and inertial navigation data. Finally, the velocity and position estimations from the proposed method are validated via actual flight test and via comparison with velocity measurement information from a PX4Flow module and a Guidance module and with locating information from movement capture system.
王亭亭, 蔡志浩, 王英勋. 无人机室内视觉/惯导组合导航方法[J]. 北京航空航天大学学报, 2018, 44(1): 176-186.
WANG Tingting, CAI Zhihao, WANG Yingxun. Integrated vision/inertial navigation method of UAVs in indoor environment. JOURNAL OF BEIJING UNIVERSITY OF AERONAUTICS AND A, 2018, 44(1): 176-186.
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2018, Vol. 44 
