Robust Imaging Sonar-based Place Recognition and  Localization in Underwater Environments

Hogyun Kim, Gilhwan Kang, Seokhwan Jeong, Seungjun Ma and Younggun Cho

Place recognition using SONAR images is an important task for SLAM in underwater environments. This paper proposes a robust and efficient imaging SONAR-based place recognition, SONAR context, and loop closure method. 

Unlike previous methods, our approach encodes geometric information based on the characteristics of raw SONAR measurements without prior knowledge or training. We also design a hierarchical searching procedure for fast retrieval of candidate SONAR frames and apply adaptive shifting and padding to achieve robust matching on rotation and translation changes. In addition, we can derive the initial pose through adaptive shifting and apply it to the ICP-based loop closure factor. 

We evaluate the SONAR context's performance in the various underwater sequences such as simulated open water, real water tank, and real underwater environments. The proposed approach shows the robustness and improvements of place recognition on various datasets and evaluation metrics.

The Video for Introduction