Junha Yoo

DIVO: Continuous-time DVL-Inertial-Visual Odometry for Unmanned Underwater Vehicles

Kyungmin Jung, Angad Bajwa, Junha Yoo, Arturo Del Castillo Bernal, James Richard Forbes

This paper presents a novel acoustic-visual-inertial odometry solution leveraging a continuous-time trajectory estimation framework for unmanned underwater vehicles. Underwater environments present unique challenges for visual localization and mapping, such as light attenuation,…Read more