Sonar Mapping and Sampling of Underwater Archaeological Excavations
Case-Study application at the Oberwartha reservoir in Saxony/Germany
Keywords:
Semi-autonomous UUV, sample collection, Orientation with sonar, self-localization, UTM coordinatesAbstract
The authors present a system for underwater 3D mapping and excavation by combining a semi-autonomous mini-submarine with a radio buoy. The system is designed for archaeological documentation where reliable underwater georeferencing is a major challenge. The buoy provides communication and sensor data to the base station, while the mini-submarine carries a ping sonar and videogrammetry equipment for 3D reconstruction. To perform a semi-autonomous dive, a fixed cable length must be selected between the submarine and the buoy, and the dive depth must be set. Therefore, a rough map of available dive depths is crucial to better specify the dive. The authors used a small sonar called Deeper to locate individual measuring points in the water depth and obtain a rough map of the water body. With this information, the authors were able to determine the number and angles of the cameras to be placed on the submarine and adjust the cable length accordingly. The cameras were then used to record the structure of the bottom of the water body and the images were processed using ORB-SLAM3 for real-time 3D reconstruction.The results showed that the system was successful in obtaining 3D maps of the underwater structures and sampling locations. The system was able to provide reliable and accurate depth measurements, allowing the authors to plan the dive in advance and avoid potential difficulties. In addition, the authors found that the system was able to operate effectively in deep water as long as sufficient light was available. Overall, the authors concluded that the semi-autonomous system for underwater 3D mapping and excavation is a promising approach that could be used in other underwater applications. The authors also suggested that future work could focus on improving the accuracy and reliability of the system, as well as integrating additional sensors and algorithms to improve performance.
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