Multi-Sonar Fusion-Based Precision Underwater 3D Reconstruction for Optimal Scan Path Planning of AUV

This paper proposes a multi-sonar fusion-based underwater three-dimensional (3D) point cloud generation method for optimal scan path planning of an autonomous underwater vehicle (AUV). 3D reconstruction based on forward-looking sonar (FLS), a crucial sensor due to its robustness in underwater environments, is essential for underwater mapping and scan path planning of AUVs. A multi-sonar fusion method using FLS and profiling sonar (PS) in a previous study can eliminate the false slope points generated due to noise and the ambiguity in the vertical field-of-view (FoV) of the FLS. However, it shows limitations depending on "the encountered yaw angle", defined as the angle between AUV's scan path direction and the front edge line of object's upper area, which cannot be easily accounted for using a two-dimensional (2D) PS map. The proposed method detects the encountered yaw angle in the current scan path and estimates the next optimal scan path where the encountered yaw angle is suitable for fusion. Subsequently, using the fused 3D reconstruction result from the optimal scan path, we propose a 3D reconstruction of PS data for fusion with the FLS. We evaluated our method in the simulator and water tank experiments. The results show that the proposed method surpasses other methods, FLS only and the conventional fusion method with the FLS and 2D PS map in both environments. Finally, the proposed method will contribute to applications such as underwater exploration and AUV navigation, which require accurate mapping and scan path planning.