4.7 Article

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

Journal

IEEE TRANSACTIONS ON ROBOTICS
Volume 39, Issue 3, Pages 1873-1892

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TRO.2022.3229842

Keywords

Commercial off-the-shelf (COTS) systems; marine robotics; sensor fusion; simultaneous localization and mapping (SLAM)

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Accurate and self-consistent bathymetric maps are necessary for monitoring changes in subsea environments and infrastructure. This article presents a method to improve map self-consistency by integrating loop-closure measurements into a commercial subsea navigation system. The integration is done without access to raw sensor measurements or proprietary models, using a white-noise-on-acceleration motion prior.
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.

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