面向无人艇对接回收的STag标记视觉导引技术

STag marking visual guidance method for USV docking

  • 摘要:
    目的 针对无人艇自主对接回收中实时位姿精准获取的问题,提出一种面向无人艇对接回收的STag标记视觉导引技术。
    方法 利用STag标记姿态稳定的特性,将其选作视觉导引中的基准标记。通过对无人艇摄像头视频流中STag标记的检测,结合摄像头的内部参数及STag标记的尺寸,融合EPnP及直接线性变换算法来解算回收装置与无人艇的相对位姿,并对其进行限幅滤波及一阶低通滤波处理,进而获得视线导引所需的横向偏距及航向偏差。
    结果 在静态性能测试中,目标检测的角度误差平均值为6.85°,距离误差平均值为0.056 m;在自主回收导引的湖上测试中,静态对接及动态对接的精度均在正负0.5 m内。
    结论 结果表明,相对于传统的无人艇对接回收方式,STag标记视觉导引可提高无人艇自主对接末端精度,提升整体回收成功率。

     

    Abstract:
    Objective Aiming at the problem of accurate real-time pose acquisition in the autonomous recovery of an unmanned surface vehicle (USV), a STag marking visual guidance method for unmanned vehicle docking and recovery is proposed.
    Methods  Due to the stable attitude characteristics of STag markers, they are selected as the fiducial markers in the visual guidance of this work. By detecting STag markers in the video stream obtained by the camera on the USV, combined with the camera's internal parameters and the size of the markers, EPnP and direct linear transformation (DLT) algorithms are fused to calculate the relative pose of the recovery device and USV. Amplitude limiting filtering and first-order low-pass filtering are then performed to obtain the required lateral offset and heading deviation for line-of-sight (LOS) docking guidance.
    Results In the static performance test, the average angular error of target detection is 6.85° and the average distance error is 0.056 m. In the guided autonomous recovery lake test, the accuracy of static and dynamic docking is within plus or minus 0.5 m.
    Conclusion Compared to traditional USV docking and recovery methods, STag marking visual guidance can enhance the terminal accuracy of USV autonomous docking and improve the overall success rate of docking and recovery.

     

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