鲍继宇, 王龙, 董新民. 硬管式无人机AAR双目视觉导航算法研究[J]. 应用光学, 2017, 38(6): 910-916. DOI: 10.5768/JAO201738.0602002
引用本文: 鲍继宇, 王龙, 董新民. 硬管式无人机AAR双目视觉导航算法研究[J]. 应用光学, 2017, 38(6): 910-916. DOI: 10.5768/JAO201738.0602002
Bao Jiyu, Wang Long, Dong Xinmin. Binocular vision navigation algorithm for AAR of flying boom UAV[J]. Journal of Applied Optics, 2017, 38(6): 910-916. DOI: 10.5768/JAO201738.0602002
Citation: Bao Jiyu, Wang Long, Dong Xinmin. Binocular vision navigation algorithm for AAR of flying boom UAV[J]. Journal of Applied Optics, 2017, 38(6): 910-916. DOI: 10.5768/JAO201738.0602002

硬管式无人机AAR双目视觉导航算法研究

Binocular vision navigation algorithm for AAR of flying boom UAV

  • 摘要: 针对硬管式无人机自主空中加油近距编队阶段的相对位置和姿态估计问题,研究了基于双目视觉的相对位姿估计算法。该算法采用Harris方法提取特征点,并对其进行快速匹配,通过Sampson方法三维重构获得特征点在摄像机坐标系下的三维坐标,以重构误差平方和最小为准则建立目标函数,利用单位四元数法求解位姿参数。最后利用仿真平台验证双目视觉位姿估计算法的有效性。结果表明:相对位置误差低于0.1 m,相对姿态误差小于0.5°,其精度满足自主空中加油相对导航性能要求。

     

    Abstract: Aiming at the estimation problem of relative position and attitude of autonomous aerial refueling(AAR) of flying boom UAV in close formation stage, the relative pose estimation algorithm based on binocular vision is studied. The algorithm uses Harris method to extract feature points and quickly matches them. The 3D coordinates of feature points in camera coordinate system are obtained by Sampson method, and the objective function is established with the minimum square sum of reconstructed error. The position and pose parameters are solved by unit quaternion method. Finally simulation platform is used to verify the effectiveness of the algorithm. Results show the relative position error is better than 0.1 m, the relative attitude error is less than 0.5°, and the accuracy meets the requirements of AAR relative navigation performance.

     

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