4.6 Article

Collaboration of Heterogeneous Marine Robots Toward Multidomain Sensing and Situational Awareness on Partially Submerged Targets

期刊

IEEE JOURNAL OF OCEANIC ENGINEERING
卷 47, 期 4, 页码 880-894

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JOE.2022.3156631

关键词

Robot sensing systems; Robots; Collaboration; Autonomous aerial vehicles; Sea surface; Multi-robot systems; Marine robots; Autonomous mission-planning; autonomy; mar-ine robotics; multidomain sensor fusion; multirobot collaborat-ion

资金

  1. DNDIDEaS grant
  2. Cellula Robotics Ltd.
  3. Irving Shipbuiliding Research Chair in Marine Engineering and Autonomous Systems

向作者/读者索取更多资源

This article discusses a multirobot system that collaboratively obtains above-water, surface, and below-water information on a floating target. The system utilizes an unmanned aerial vehicle, unmanned underwater vehicle, and unmanned surface vehicle to autonomously survey and gain situational awareness on the target from a safe distance. The system's contributions include cross-domain robotic collaboration, autonomous mission-planning, and data fusion from heterogeneous robots.
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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