In the development of autonomous marine robotics (e.g., Autonomous Surface Vehicles, Underwater Unmanned Vehicles), a major component of robot decision-making lies in intelligent path-planning. This research is in collaboration with the US Navy and aims to combine global and local path-planning methods to establish a multi-layered strategy utilizing a priori knowledge of an aquatic area and vehicle dynamics with the real-time detection of unmapped obstacles and hazards.
Funding has been provided by NAVSEA, the Naval Engineering Education Consortium (NEEC), and the New Hampshire Sea Grant.
Faculty Researcher and Contact: Dr. May-Win Thein
