Yang Hongbo, Xu Zhizun, Jia Baozhu
Maritime College, Guangdong Ocean University, Zhanjiang 524000, China.
Sensors (Basel). 2022 Jul 20;22(14):5418. doi: 10.3390/s22145418.
Underwater positioning presents a challenging issue, because of the rapid attenuation of electronic magnetic waves, the disturbances and uncertainties in the environment. Conventional methods usually employed acoustic devices to localize Unmanned Underwater Vehicles (UUVs), which suffer from a slow refresh rate, low resolution, and are susceptible to the environmental noise. In addition, the complex terrain can also degrade the accuracy of the acoustic navigation systems. The applications of underwater positioning methods based on visual sensors are prevented by difficulties of acquiring the depth maps due to the sparse features, the changing illumination condition, and the scattering phenomenon. In the paper, a novel visual-based underwater positioning system is proposed based on a Light Detection and Ranging (LiDAR) camera and an inertial measurement unit. The LiDAR camera, benefiting from the laser scanning techniques, could simultaneously generate the associated depth maps. The inertial sensor would offer information about its altitudes. Through the fusion of the data from multiple sensors, the positions of the UUVs can be predicted. After that, the Bundle Adjustment (BA) method is used to recalculate the rotation matrix and the translation vector to improve the accuracy. The experiments are carried out in a tank to illustrate the effects and accuracy of the investigated method, in which the ultra-wideband (UWB) positioning system is used to provide reference trajectories. It is concluded that the developed positioning system is able to estimate the trajectory of UUVs accurately, whilst being stable and robust.
水下定位是一个具有挑战性的问题，这是由于电磁波的快速衰减以及环境中的干扰和不确定性。传统方法通常采用声学设备来定位无人水下航行器（UUV），但这些方法存在刷新率低、分辨率低且易受环境噪声影响的问题。此外，复杂地形也会降低声学导航系统的精度。基于视觉传感器的水下定位方法的应用受到了阻碍，这是因为由于特征稀疏、光照条件变化和散射现象，获取深度图存在困难。在本文中，基于激光雷达相机和惯性测量单元，提出了一种新型的基于视觉的水下定位系统。激光雷达相机受益于激光扫描技术，能够同时生成相关的深度图。惯性传感器将提供其高度信息。通过融合来自多个传感器的数据，可以预测UUV的位置。之后，使用光束平差法（BA）重新计算旋转矩阵和平移向量以提高精度。在水箱中进行了实验，以说明所研究方法的效果和精度，其中使用超宽带（UWB）定位系统提供参考轨迹。结果表明，所开发的定位系统能够准确估计UUV的轨迹，同时具有稳定性和鲁棒性。
