Energy-Efficient Integrated Motion Planning and Control for Unmanned Surface Vessels

This brief studies the online simultaneous motion planning and control of unmanned surface vessels (USVs) with multiple practical constraints. An online economic model predictive control (EMPC)-based integrated planning and control framework is developed to greatly reduce energy consumption. In particular, a novel heuristic terminal cost guarantees both the planning control performance and facilitates the online optimization, and an improved cross-entropy (CE)-based optimization algorithm speeds up the solving of the nonconvex economic optimization problem. Experimental results show that the proposed integrated planning and control approach can be implemented in real-time with the online optimization frequency of 100 Hz, and comparative studies indicate that it can save energy up to almost 18%.