Minh Quan Le
Contact information
Location: Building 193, Room 315, Desk 45
Thesis title
Learning-based control for underwater robots
Research overview
Underwater robots play a vital role in ocean exploration however, their operation faces challenges in the unpredictable underwater environment. My research addresses these issues by proposing the integration of Deep Reinforcement Learning with Model Predictive Control for individual Autonomous Underwater Vehicle (AUV) control and a distributed learning model for multi-AUV swarm coordination. The study aims to enhance adaptability in dynamic conditions and efficiently manage limited communication bandwidth, contributing to advancements in underwater robotics through practical feasibility assessments in both simulated and real-world scenarios.
Supervisors
Qualifications
BSc in Mechatronic Engineering