融合激光雷达和惯性导航的船舶靠离泊高精度定位方法

High-precision berthing and unberthing ship positioning method by fusing LiDAR and inertial navigation system

  • 摘要:
    目的 为了满足船舶靠离泊过程中近距离高精度感知的需求,提出一种融合激光雷达和惯性导航系统的高精度定位方法。
    方法 首先,构建船舶航行的多坐标转换和时间配准算法,实现感知设备在时间和空间上的统一,并对采集的点云数据进行校正和滤波处理;其次,提出一种改进的随机采样一致性算法(RANSAC),通过引入泊位高程来确定聚类阈值,并优化聚类成本函数,从而降低点云数据随机性对岸线检测精度的影响;最后,将识别的岸线交集作为泊位的特征点,辅助无人艇(USV)进行定位,并通过实船验证该方法的感知效果。
    结果 实验结果表明,该定位方法可为船舶提供误差小于0.256 m的定位信息,同时在实际环境中对各种干扰有较强的适应性。
    结论 改进RANSAC船舶靠离泊定位方法在点云数据质量较差的前提下,仍能保证较高的定位精度。

     

    Abstract:
    Objective Addressing the requirement for precise sensing during ship berthing and unberthing at close range, we propose a high-precision berthing and unberthing positioning method by fusing LiDAR with an inertial navigation system.
    Methods Initially, we develop a multi-coordinate conversion and time registration algorithm for ship navigation, achieving the temporal and spatial unification of various sensing devices while correcting the collected point cloud data. Subsequently, we introduce an enhanced random sample consensus (RANSAC) berth shoreline detection method which mitigates the impact of point cloud data randomness on shoreline detection accuracy by considering berth elevation and optimizing the clustering cost function. The identified shoreline intersection serves as a characteristic point for berthing, aiding unmanned surface vehicles in positioning. Finally, the effectiveness of the proposed method is validated through real ship experiments.
    Results The experimental outcomes demonstrate that this positioning method yields positioning information for ships with an error of less than 0.256 m and exhibits strong adaptability to various interferences in real-world environments.
    Conclusion The improved RANSAC method for ship berthing and unberthing can obtain high positioning accuracy even when the quality of the point cloud data is poor.

     

/

返回文章
返回