A robust return-home strategy for a long-range AUV operating beneath ice
Creators: name: King, PD
Publisher: name: University of Tasmania
Year: 2024

description: Autonomous Underwater Vehicles (AUVs) are free-swimming robots that can explore regions of the ocean beyond the capabilities of ships or tethered vehicles. Their independence al?lows them to work deep, over long distances, and beneath the cover of floating ice. This independence comes at a cost as they need to navigate and position themselves with no external aids or reference. This work aims to improve the ability of an AUV to conduct ex?ploratory missions in un-surveyed and high-risk areas, such as beneath the ice in Antarctica, and return to a known safe recovery location. AUVs suffer from navigational drift making it dangerous to conduct these missions in their current state since the presence of ice can hinder the use of external navigational aiding. A solution to this problem is to allow the AUV to venture into an area, while accumulating error, then re-trace the inward path on the way out; if path was safe to get in then it is safe to get out. Navigation is driven by the registration of sensor readings to a repository of data collected on the path in. To enable this a methodology known as teach-and-repeat, taken from terrestrial robotics with application in extraterrestrial exploration, was developed and tested. <br>AUVs rely on acoustics. A methodology to generate image views from sonar data was developed, based on existing work in terrestrial robotics utilising visual cameras. An adaption of teach-and-repeat (TR) was developed to navigate an AUV along a previously traversed path through image registration and tested successfully in the field. The AUV navigated solely on the sonar information and its mapping to the initial path. The localisation was topological and relative only to the taught path, and thus was not affected by the inherent errors in global positioning. <br>Further development applied this concept to an AUV collecting 3D bathymetry data, where subsets of data collected at different times could be compared to derive a likelihood that they were of the same area of the seafloor. This capability broadens the potential applicability of TR. The methodology was developed and tested on data gathered in situ during an AUV deployment to the Thwaites Glacier in Antarctica, using real data collected during an under?ice deployment. <br>The key advantage of the methods developed in this work is their robustness, relying only on relative navigation to a taught path, known to be safe. The key findings of this work are the effectiveness in utilising either sidescan or bathymetric sonars in registering views of the seafloor against prior data. The performance in terms of aiding localisation improves on non-aided conventional navigation relying solely on dead reckoning. The implemented TR navigation system was validated and performed well in the field, providing robust and reliable navigation and an improved ability to return the AUV to a set location. Given the exploratory nature of under ice missions, the method is more generally applicable to this particular mission scope than current state of the art positioning methods, such as SLAM, which rely on data overlaps to close the loop on errors