遥控水下航行器
形势意识
机器人
计算机科学
实时计算
水深测量
无人机
水下
移动机器人
海洋工程
运动规划
节点(物理)
弹道
同时定位和映射
人工智能
工程类
计算机视觉
航空航天工程
海洋学
物理
地质学
地图学
天文
地理
结构工程
作者
Joel Lindsay,Jordan Ross,Mae Seto,Edward Gregson,Alexander Moore,Jay Patel,Robert Bauer
标识
DOI:10.1109/joe.2022.3156631
摘要
This article reports on a multirobot system that collaboratively obtains above-water, surface, and below-water information on a floating target. This capability allows a ship to autonomously survey and obtain situational awareness on a floating unresponsive target from a safe stand-off before inspecting it more closely or navigating around it. The target could be another ship, structure, or a navigational obstruction like an iceberg. The proposed solution is a collaborative system with an unmanned aerial vehicle (UAV), an unmanned underwater vehicle (UUV), and an unmanned surface vehicle (USV). The UAV captures visual imagery to create a 3-D model of the target's above-water geometry using photogrammetry. The UUV surveys the target's submerged hull with integrated imaging and profiling bathymetric sonars. The USV hosts an intelligent mission-planning node which manages the robotic collaboration in a centralized architecture by autonomously planning and distributing the missions for the UUV and UAV. The intelligent node also adaptively plans the USV's trajectory to support the other autonomous assets, specifically reducing and bounding the UUV's state-estimate error through collaborative localization. The resulting above- and below-water sensor data is fused at the waterplane, using a sliding correlation algorithm, to yield a 3-D representation of the floating unresponsive target. The contributions from this article include the cross-domain robotic collaboration and autonomous mission-planning toward acquiring and fusing data from heterogeneous robots. The autonomous mission-planning and data-merging algorithms are presented. The setup and results from simulations and in-water testing with an UUV, USV, and UAV are described.
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