Underwater Acoustic Localization using pose-graph SLAM

Current acoustic localization systems for Autonomous Underwater Vehicles (AUV) rely on acoustic beacons at known positions. We present a method that combines rangeonly acoustic measures and odometry data into a factor graph structure, able to compute the AUV localization while estimating the position of the acoustic beacons without having previous information about their position. We designed several missions and carried them out in a real environment to gather data to test our algorithm offline. The output of this work is a pose-graph SLAM algorithm that combines the AUV internal measurements (i.e. DVL, IMU, and depth) with acoustic ranges from static beacons to estimate both the AUV state and the beacon’s position.