Research On UAV Indoor Positioning Technology Based On The Fusion Of Vision And IMU

With the rapid development of unmanned aerial vehicle technology,the application of unmanned aerial vehicles has become more and more extensive,from the military field to gradually diversify to various professional fields such as aerial photography,inspection,and drone logistics.With the continuous expansion of UAV application scenarios,how to accurately locate in the absence of GPS signals is a general trend in the future development of UAV technology.Traditional indoor positioning technologies such as RFID,WiFi,and infrared signals have problems such as high facility costs.The positioning of environmental perception through visual sensors has become the first place for accurate positioning of drones in indoor environments due to its low system cost and small size.Program.The focus of this paper is the research of UAV indoor positioning technology based on the fusion of vision and IMU.The main research contents are as follows:（1）Analyze the measurement characteristics of the sensor,deeply study the UAV attitude and the working characteristics of the inertial measurement unit,and lay the foundation for the research of attitude and positioning fusion algorithm.（2）The vision-based positioning process of UAV is introduced.The basic principles of image corner detection,optical flow tracking,mismatched point removal,and position output are studied.The algorithm design based on FAST corner points is completed,and the optical flow tracking and mismatch point removal algorithm is improved by using IMU information.Experiments show that the improved algorithm in this paper improves the calculation efficiency and accuracy.（3）Research the IMU positioning,use the gyroscope and accelerometer to get the attitude angle of the UAV,and conduct theoretical derivation and analysis of the commonly used attitude calculation algorithms.The focus is on the Kalman filter,which is the most widely used in the information fusion algorithm,to improve the Kalman filter for the attitude calculation in the magnetic interference environment,and provide reliable attitude information and horizontal position information for IMU positioning.（4）Fuse the speed and position information of the UAV,and use the extended Kalman filter to fuse the position information calculated by the accelerometer and the ultrasonic sensor to obtain the horizontal position and vertical height of the UAV.The algorithm is verified based on the self-developed flight control system,and the results show that the algorithm can improve the positioning accuracy of the UAV in the indoor environment and meet the actual needs of UAV indoor flight.