Underwater SLAM based on object recognition using YOLO in acoustic images

This paper proposes underwater simultaneous localization and mapping (SLAM) with 3D reconstruction by applying YOLOv7 to acoustic images. In underwater exploration, acoustic cameras, which are called the next generation of ultrasonic sensors, are gradually being applied, and underwater SLAM technologies based on 3D reconstruction with acoustic cameras have been proposed. However, many limitations remain in the accuracy of maps. In this study, we propose a novel approach to improve SLAM accuracy by applying detection results from YOLOv7 in acoustic images to the 3D reconstruction. We utilized the detected objects by YOLOv7 as feature information applied to iterative closest point (ICP)-based SLAM.