Research of Autonomous Vision-Based Absolute Navigation for Unmanned Aerial Vehicle

被引：0
|
作者：
Huang Lan [1 ]
Song Jianmei [1 ]
机构：
[1] Beijing Inst Technol, Sch Aerosp Engn, Beijing, Peoples R China
来源：
2016 14TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION, ROBOTICS AND VISION (ICARCV) | 2016年
关键词：
Unmanned aerial vehicle; Vision-based absolute navigation; Observability; Condition number; Extended Kalman Filter; RELATIVE NAVIGATION; INERTIAL NAVIGATION; FLIGHT;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper makes research on two schemes of autonomous vision-based absolute navigation for Unmanned Aerial Vehicle (UAV): the Imaging Position of Landmark/Altimeter/IMU (IPLAI) based navigation, and the Imaging Position of Landmark/Optical Flow/Altimeter/IMU (IPLOFAI) based navigation. Firstly, the models of two autonomous vision-based absolute navigation systems are established. Secondly, the observability matrixes of two navigation systems are derived according to the differential geometric theory, and then the observability of the two navigation systems based on the condition number of the observability matrixes is carried on the quantitative analysis. Thirdly, the corresponding navigation EKFs (Extended Kalman Filters) are designed to get the absolute position and velocity estimations of the UAV. At last, the correctness of the observability analysis and the designed navigation filters of the two navigation systems are verified through simulation experiment.
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页数：6
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