This paper proposes the Risk-Aware SAC (RA-SAC) algorithm for unmanned surface vehicle (USV) path planning in the presence of high-speed dynamic obstacle interference. This method integrates risk perception, obstacle motion state extrapolation and heading constraint reward into the SAC framework. While preserving the entropy-maximization mechanism of SAC, it enhances long-horizon obstacle avoidance awareness through reward sha...

Model-aided navigation is a key approach for enhancing the positioning accuracy of autonomous underwater vehicles (AUVs). However, its precision is often degraded by model-based velocity errors arising from attitude-induced deviations and uncertainties in the mapping between propeller rotational speed and vehicle velocity. To overcome these limitations, this study proposes an attitude-compensated and acoustics-calibrated model...