Underwater 3D Reconstruction Based on Geometric Transformation of Sonar and Depth Information

3D reconstruction is of vital importance to detect and monitor the underwater environment. A method based on geometric transformation of mechanical scanning sonar and depth information is proposed, in which the point cloud data from sonar and depth gauge are acquired to reconstruct the underwater 3D environment. However, noise and interference can affect the measurement of sonar, and movement of sonar during measurement can lead to distortion of the received data. Meanwhile, translation and rotation movement of sonar head may happen when ROV dives which can lead to different body reference coordinates of different scanning. To solve this, pre-processing and motion compensation are implemented at first, and underwater matching correction algorithm is used to calculate the translation and rotation of the sonar head. Then the inverse operation is implemented to convert the scan data of every depth into the same coordinate reference system. Finally, surface reconstruction of point clouds from sonar the depth information are used to reconstruct underwater environment based on MLS (Moving Least Square Method) using PCL (Point Cloud Library). Water tank experiments verify the effectiveness of the proposed method.