Underwater Navigation

Underwater navigation research focuses on enabling autonomous underwater vehicles (AUVs) to reliably navigate complex and often poorly-understood environments. Current efforts concentrate on improving robustness and accuracy through sensor fusion (e.g., integrating inertial navigation systems with Doppler velocity logs and laser-based loop closures), advanced algorithms like extended Kalman filters and neural networks (including LSTM and PPO), and bio-inspired approaches leveraging magnetic field data. These advancements are crucial for enhancing the capabilities of AUVs in various applications, including underwater mapping, inspection, and exploration, ultimately leading to more efficient and reliable subsea operations.