An enhanced path planning method for unmanned surface vehicle based on JPS plus and goalbounding algorithm

The path planning issue in complex environments remains an challenging problem in the field of unmanned surface vehicle (USV) navigation due to its complexity and the nature of nondeterministic polynomial-time hard (NP-hard). Aiming at generating a safe path for the USV within tractable time, this paper proposes an enhanced path planning method via integrating JPS+ algorithm and the goalbounding algorithm. Firstly, principles of the JPS+ and goalbounding algorithms are respectively analysed and investigated in this study. Subsequently, the application platform of the proposed path planning approach for USV is established via combining the YimaEnc electronic chart with WinForm dialog. Finally, the performance of the proposed method is validated through some numerical simulations against some other well-known path planning methods. The simulation results confirm that the proposed method performs superior to the artificial field method and A* algorithm in terms of the computation time and the path safety. Besides, the superiority of the proposed method over the artificial field method and A* algorithm is more significant in the long-distance path planning scenarios as far as the computation time is concerned.