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Deep Inertial Underwater Odometry System

Underwater 6-DOF odometry is an essential technology for robotics, navigation, and motion-based control systems. Existing solutions have issues to be solved: complicated sensor configurations and limited usage conditions. This paper presents a robust, stand-alone, light-weighted IMU-based underwater odometry system, referred to as deep inertial underwater odometry (DIUO). Our system is based on an inertial odometry technique based on deep learning used in the air. The main issue to be solved is the ground-truth data collection of inertial underwater odometry for supervised learning. Therefore, we design a stick-shaped jig that rigidly connects a fiducial marker and an IMU for the data collection. Inertial underwater odometry is computed by tracking the marker with a motion capture system in the air and using the rigid transformation from the marker to the IMU. Furthermore, the performance analysis of DIUO was conducted with several motions in the evaluation. Finally, we discuss limitations and perspectives.