国外水面无人艇环境感知技术前沿进展

doi:10.12382/bgxb.2024.0860

摘要/Abstract

摘要：

水面无人艇(Unmanned Surface Vehicles,USV)具有机动性好、隐蔽性强、活动范围广等优点,在侦查、反潜、搜救等任务中具有广阔的应用前景,而环境感知技术是USV执行任务的基础,受到广泛关注。对国外USV环境感知技术发展现状进行调研,通过具体案例对USV环境感知技术进行定义并剖析任务难点;结合USV使用的感知设备,从单模态感知和多模态感知两个角度具体分析USV感知技术研究现状;总结分析USV暂未解决的难点并对USV环境感知技术发展给予展望。

关键词: 水面无人艇, 感知技术, 多模态感知, 雷达

Abstract:

Unmanned surface vehicles (USVs) have high mobility,strong concealment,and extensive operational range,making them highly suitable for performing a wide array of tasks such as reconnaissance,anti-submarine warfare,search and rescue.Environmental perception technology,crucial for the operation of USVs,has attracted considerable attention.This paper conducts a survey on the development status of environmental perception technology for USVs at abroad,and define and analyzed the challenges in USV environmental perception through specific case studies.The current state of research on USV environmental perception technology is analyzed from the perspectives of both unimodal and multimodal perception,considering the sensory equipment utilized by USVs.Finally,the unresolved challenges in USV environmental perception technology are summarized,and its future development is prospected.

Key words: unmanned surface vehicle, perception technology, multi-modal perception, radar

李丹, 于邵祯, 杨华东. 国外水面无人艇环境感知技术前沿进展[J]. 兵工学报, 2024, 45(S2): 97-104.

LI Dan, YU Shaozhen, YANG Huadong. Progress on Environmental Perception Technology of Foreign Unmanned Surface Vehicles[J]. Acta Armamentarii, 2024, 45(S2): 97-104.

图/表 11

图1 海上猎人号示意图[2]

Fig.1 Schematic diagram of the Sea Hunter

表1 USV常见传感器

Table 1 Common Sensors for unmanned surface vehicle

传感器类型	探测距离	信息内容	优点	缺点
可见光传感器	10~5km	可见光视频	分辨率高、信息内容丰富	易受干扰,黑暗环境无法工作
红外传感器	10~500m	红外视频	抗干扰能力强、可在夜间工作	分辨率较低,探测范围有限
扫描雷达	100~10km	雷达点云	范围广、抗干扰能力强	信息内容较少、精度低
激光雷达	1~100m	雷达点云	精度高	探测范围较弱
航海雷达	1~100km	雷达点云	探测范围广	精度低
惯导		船舶姿态、位置	自主导航、结构简单	计算量大、误差累积

图2 USV主要工作环境

Fig.2 Main working environments for unmanned surface vehicles

图3 凸优化模型的图像增强方法效果[14]

Fig.3 Image enhancement effect of improved convex optimization model[14]

图4 红外海面小目标识别效果[19]

Fig.4 Result of thermal object detection[19]

图5 USV目标跟踪效果[22]

Fig.5 Result of USV Object Tracking[22]

图6 航海雷达SLAM建图[25]

Fig.6 Maritime radar SLAM mapping[25]

图7 使用激光雷达在实际港口避障效果图[31]

Fig.7 Obstacle avoidance effect in actual ports using LiDAR[31]

图8 结合视觉传感器与雷达的环境感知

Fig.8 Environmental perception scheme combining visual sensors and radar

图9 结合AIS与雷达的环境感知

Fig.9 Flowchart of environmental perception combining AIS and radar

图10 遮挡情况下的雷达与AIS[43]

Fig.10 Radar and AIS under occlusion conditions[43]

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