Robust Underwater Localization Using Acoustic Image Alignment for Autonomous Intervention Systems

Abstract

Acoustic imaging sonar can be used as important navigation sensors for underwater intervention systems as they consistently provide spatial information about the surrounding environment, even in limited visibility conditions. However, acoustic imaging sonars are known for high spatial ambiguity and low resolution of their measurements, which makes it challenging to obtain precise navigational information. This paper presents a novel localization method based on sensor fusion using an integrated IMU-DVL system and an acoustic imaging sonar. A sonar simulator is implemented and used to estimate the pose of the robot based on a single acoustic image, and it is formulated as an image alignment problem between a simulated acoustic image and an actual acoustic image. For this, an approximate nearest neighbor search method is employed for initial pose estimation, and a newly developed acoustic image alignment method is applied to obtain more accurate results in a continuous pose space. These methods are then combined to construct an integrated localization system using all the navigation sensors on the robot. Its feasibility and utility of the proposed approach is shown through an experimental validation in a test tank.