无人机室内视觉/惯导组合导航方法

针对室内无卫星定位下的无人机自主导航问题，提出了一种融合惯导、光流和视觉里程计的组合导航方法。在速度估计上，采用基于ORB特征的光流法，该方法可以实时地估计出无人机的三轴线速度信息。方法采用基于特征点的稀疏光流，对金字塔Lucas-Kanade光流法进行了改进，采用前后双向追踪和随机采样一致的方法提高特征点追踪精度。在位置估计上，采用视觉/惯导融合的视觉里程计，以人工图标法为主，融合视觉光流信息和惯导数据实现无人机定位。通过与运动捕捉系统的定位信息、Guidance和PX4Flow导航模块的测速信息进行对比，以及实际的飞行测试，验证本文方法的可行性。

Integrated vision/inertial navigation method of UAVs in indoor environment

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 pyra-mid 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 po-sition 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 veloc-ity measurement information from a PX4Flow module and a Guidance module and with locating information from movement capture system.