IEEE

Sim-to-Real Transfer for AUV Fault Control with Deep Reinforcement Learning

Abstract: This paper presents a methodology for the sim-to-real transfer of deep reinforcement learning (DRL) models for fault-tolerant control (FTC) in autonomous underwater vehicles (AUVs). The ...
IEEE

Integrated Energy Optimization and Stability Control Using Deep Reinforcement Learning for ...

Abstract: This study presents an innovative solution for simultaneous energy optimization and dynamic yaw control of all-wheel-drive (AWD) electric vehicles (EVs) using deep reinforcement learning ...