地面目标特征识别与无人飞行器位姿估计

针对小型无人飞行器位置姿态估计问题,提出了一种基于视觉图像目标特征的相对位姿估计算法。应用Camshift算法获取目标初始位置,利用非线性尺度空间下的KAZE特征进行跟踪区域特征点提取,与源目标特征点进行匹配,得到精确的目标位置信息,实现了在图像平面内的目标快速跟踪,并得到机体轴系下无人飞行器与目标间相对位置和姿态角的估计值。对算法进行了实验验证,具有优良的跟踪性和实时性。

Feature Recognition of Ground Target and Position and Attitude Estimation for Unmanned Aerial Vehicle

To aim at the problem of position and attitude estimation for UAV, a relative position and attitude estimation algorithm based on target features in image is proposed. The initial location of the target was obtained with Camshift algorithm. The feature points in tracking area was picked up with KAZE features based on the nonlinear scale space, which are used to match with the feature points of the source target. The exact location of the target can be obtained. The target can be tracked quickly in the picture plane. The estimation of relative position and attitude between the unmanned aerial vehicle and target was conducted in the body frame of axes. Some experiments were fulfilled for the verification of the algorithm. The results show that the estimation error of the proposed algorism is little. This algorithm has strong tracking and real-time performance.