针对在GPS信号薄弱或者缺失的室内环境下定位悬停问题,文中对于传统稀疏光流法假设条件很难满足的缺点,将改进ORB算法与特征光流算法相结合来估计出飞行器的光流信息数据,并将光流信息数据与飞行器的惯导数据相融合,消除了由于飞行器自身抖动产生的对飞行器速度的错误估计,提高了室内飞行器姿态稳定性。通过自行搭建的试验平台验证了文中提出方法的可行性。

For the problem of positioning hovering under weak or missing GPS signals, this paper combines the improved ORB algorithm with the characteristic optical flow algorithm to estimate the optical flow of the aircraft for the shortcomings of the assumption that the traditional sparse optical flow method is difficult to satisfy. The fusion of the optical flow information data with the inertial navigation data of the aircraft eliminate the erroneous estimation of the speed of the aircraft due to the jitter of the aircraft itself and improve the attitude stability of the indoor aircraft. The feasibility of the method presented in this paper is verified by a self-built experimental platform.