Trade-Off Between USBL Update Rate and Pose Estimation Accuracy in Factor-Based SLAM

Accurate underwater localization and mapping is crucial for applications such as autonomous ocean exploration and environmental monitoring. However, due to environmental disturbances and poor visibility, underwater navigation remains challenging. Acoustic positioning systems, such as ultra-shortbaseline (USBL), address this problem with the downside of increasing infrastructural and energy costs. This study examines the trade-off between USBL update rate and pose estimation accuracy. We demonstrate that even infrequent USBL updates as sparse as once every 10 seconds can substantially improve local- ization performance when fused with inertial measurement unit (IMU) data and landmark observations through a smoothing- based Simultaneous Localization and Mapping (SLAM) approach.