Simultaneous localization and mapping (SLAM) is a critical capability for any autonomous
underwater vehicle (AUV) in various underwater applications, including infrastructure inspection and
seabed exploration. However, achieving robust and accurate state estimation in such environments remains a
significant hurdle. This is primarily attributable to the inherent scarcity of geometric features in the subsea
environment itself and the limited field of view (FoV) of imaging sonar used for feature acquisition. These
factors collectively elevate the probability of iterative closest point (ICP) degeneracy, a frequent challenge in
most SLAM solutions. To overcome this limitation, this study proposes a method that actively adjusts the
imaging sonar
Geonwoo Park: Division of Advanced Nuclear Engineering, Pohang University of Science and Technology (POSTECH),
77 Cheongam-ro, Nam-gu, Pohang-si, Gyeongbuk 37673, Republic of Korea
Dongsub Kim, Bonchul Ku, Seungwon Ham and Son-Cheol Yu: Department of Convergence IT Engineering, Pohang University of Science and Technology (POSTECH),
77 Cheongam-ro, Nam-gu, Pohang-si, Gyeongbuk 37673, Republic of Korea
Sungduk Kim and Jinbeom Kim: Maritime RD Center, LIG Nex1, 333 Pangyo-ro, Bundang-gu, Seongnam-si,
Gyeonggi-do 13488, Republic of Korea
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