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Improving Self-Consistency in Underwater Mapping Through Laser-Based Loop Closure

delete2023-06-01
delete7
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OA
AI
T
Thomas Hitchcox *
J
James Richard Forbes
DOI:10.1109/TRO.2022.3229842delete
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Abstract

Abstract

En 中文
Accurate, self-consistent bathymetric maps are needed to monitor changes in subsea environments and infrastructure. These maps are increasingly collected by underwater vehicles, and mapping requires an accurate vehicle navigation solution. Commercial off-the-shelf (COTS) navigation solutions for underwater vehicles often rely on external acoustic sensors for localization; however, survey-grade acoustic sensors are expensive to deploy and limit the range of the vehicle. Techniques from the field of simultaneous localization and mapping, particularly loop closures, can improve the quality of the navigation solution over dead reckoning, but are difficult to integrate into COTS navigation systems. This article presents a method to improve the self-consistency of bathymetric maps by smoothly integrating loop-closure measurements into the state estimate produced by a commercial subsea navigation system. Integration is done using a white-noise-on-acceleration motion prior, without access to raw sensor measurements or proprietary models. Improvements in map self-consistency are shown for both simulated and experimental datasets, including a 3-D scan of an underwater shipwreck in Wiarton, ON, Canada.
Keywords:
Commercial off-the-shelf (COTS) systems
marine robotics
sensor fusion
simultaneous localization and mapping (SLAM)

Journal

IEEE Transactions on Robotics cover
IEEE Transactions on Robotics
IF:
10.5
Papers:
3.3K
Citations:
2.8W

Organization

M
McGill University
Scholars:
5.5W
Papers: 4.9W
Citations: 7.0W