Principal Investigator Dick Yue
Co-investigator Yuming Liu
Project Website http://oe.mit.edu/index.php?option=com_content&task=view&id=169&Itemid=122
We envisage a scenario in the near future that a fleet of agile unmanned surface vessels (USV), capable of cruising at high speed and following optimized courses through severe environmental conditions, can carry payloads and/or perform missions heretofore impossible or too dangerous for manned ships.
Based on real-time sensing and forecasting of the environment and other factors, and optimum autonomous control, such vessels are able to make rapid maneuvers to negotiate or evade extreme wave conditions and/or hostile pursuers. The surface vessels allow favorable payload to fuel requirements compared to airborne (or submarine) platforms. On the other hand, the possibility of these vessels serving as platforms for drone airplanes or AUVs, and even themselves becoming airborne or submerged at a certain phase of the mission may provide a powerful paradigm shift in naval operations.
The realization of the above scenario requires the development and integration of a number of capabilities all to be performed in real time: (1) sensing of the local wave field; (2) forecasting of the local wave field; (3) prediction of the vessel responses in waves; and (4) control and optimization of the vessel(s) and course. Recent developments in each of these areas, especially in sensing and forecasting of nonlinear wave fields, have substantially increased the possibility for this to be achieved.
The objectives of this study are: (i) to develop a virtual simulation environment to demonstrate the feasibility of applying advanced technologies in these areas to enable substantial improvements in operational capability for single/multiple unmanned/manned surface vehicles traveling under stressing environmental conditions; (ii) to identify the key developments necessary for the realization of this capability in the near future; and (iii) (ii) to develop the technologies in the bottleneck areas, especially in wave prediction, to bring this capability to real-time applications in realistic environments.