Research On Quadrotor UAV Based On Multi-Sensor Fusion Indoor Autonomous Flight Technology

With the continuous development of unmanned technology,quadrotor UAV has been widely favored by people due to its small size,flexible maneuverability,easy installation and many other advantages.At present,the outdoor flying technology of drones has become more and more mature,but in the unknown indoor environment,because GPS signals are easily interfered and cannot provide accurate positioning information,the indoor flight of drones is greatly restricted.Therefore,this thesis designs a quadrotor UAV indoor flight platform based on multi-sensor fusion,which can acquire the position information of the aircraft in real time and build a forward flight channel to achieve autonomous flight of indoor corridors.(1)For the indoor GPS signal rejection scenario and the structural characteristics of the micro-UAV,the overall scheme design of the quadrotor UAV flight platform is carried out,and the hardware selection and software platform construction are completed;the control model of the quadrotor UAV is studied;the control principle of attitude and position controller is analyzed,and the stability of cascade PID control system is verified by Simulink simulation platform.(2)The external control mode of the quadrotor drone is analyzed,and the Gazebo simulation platform and real machine flight experiments are used to prove the effectiveness of the external control method;the acquisition and processing of laser radar point cloud data are completed in the dormitory corridor;the principle of the Cartographer laser SLAM algorithm is studied,and the shortcoming of the original algorithm in the loopback detection stage is improved,the comparison experiments of positioning and mapping are carried out in the simulation scenario,indoor corridor and closed room,the results show that the real-time and accuracy of the improved algorithm are significantly improved.(3)The joint calibration model of lidar and monocular camera is constructed,at the same time,the checkerboard joint calibration experiment is completed,according to the calibration results,the internal and external parameter matrices of the camera are solved;image processing techniques such as edge detection and Hough transform are used to extract the key boundaries of the indoor environment feature,the position coordinates of the vanishing point VP on the image plane is estimated,and the safe flight area of the UAV is determined;the point cloud data and image information are fused to construct the forward flight channel of UAV,and the forward flight experiment is completed in the laboratory corridor.(4)The circular flight experiment of the quadrotor UAV in Offboard mode proves that the flight control system is stable and reliable in the external control mode;the improved Cartographer algorithm is used to complete indoor positioning and mapping experiments,and the positioning errors are analyzed,the results show that the positioning accuracy of the algorithm can meet the requirements of indoor UAV flight;finally,combined with the flight path construction method,real aircraft flight experiments are carried out in the indoor corridor scenarios to verify the effectiveness of the indoor autonomous flight strategy of UAV.