无人水面快艇（USV）需实时感知动态障碍物以适应多变海况。但依赖单帧激光雷达的导航方法未充分考虑USV速度和转向受限等动力学特性，易产生运动冲突。为此，研究融合激光雷达的无人水面快艇导航技术。采用激光雷达前后帧数据融合策略，构建消除探测盲区的环境模型。结合环境模型和USV的动力学特性，采用动态窗口法，实时评估USV的速度和转向组合，选择最优组合以实现自主避障和高效导航。实验结果显示，该技术可以精准获取障碍物位置以及方向信息；在面对会遇、对遇、追越等多种动态障碍物时，能够迅速响应并规划出安全的避障路径，成功导航出最佳避障路径。
Unmanned surface speedboats (USVs) need to sense dynamic obstacles in real time to adapt to changing sea conditions. However, the navigation method relying on single-frame liDAR does not fully consider the dynamic characteristics of USV such as speed and steering limitation, which is easy to produce motion conflict. Therefore, the navigation technology of unmanned surface boat and speedboat based on LiDAR is studied. The environment model of eliminating detection blind area is constructed by using the data fusion strategy of front and rear frames of LiDAR. Combining the environment model and the dynamics characteristics of USV, the dynamic window method is used to evaluate the speed and steering combination of USV in real time, and select the best combination to achieve autonomous obstacle avoidance and efficient navigation. The experimental results show that the technology can accurately obtain the position and direction information of obstacles; In the face of a variety of dynamic obstacles, such as encounter, encounter, and pursuit, it can respond quickly and plan a safe obstacle avoidance path, and successfully navigate the best obstacle avoidance path.
2025,47(11): 118-121 收稿日期：2025-2-18
DOI：10.3404/j.issn.1672-7649.2025.11.020
分类号：TP242
基金项目：河北省教育厅科学研究项目（QN2024113）
作者简介：张兰(1988-),女,硕士,讲师,研究方向为定位算法优化、导航技术、无线通信技术
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