Mission planning and performance verification of an unmanned surface vehicle using a genetic algorithm

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Mission planning and performance verification of an unmanned surface vehicle using a genetic algorithm

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Jihoon Park / Sukkeun Kim / Geemoon Noh / Hyeongmin Kim / Daewoo Lee / Inwon Lee

This study contains the process of developing a Mission Planning System (MPS) of an USV that can be applied in real situations and verifying them through HILS. In this study, we set the scenario of a single USV with limited operating time. Since the USV may not perform some missions due to the limited operating time, an objective function was defined to maximize the Mission Achievement Rate (MAR). We used a genetic algorithm to solve the problem model, and proposed a method using a 3-D population. The simulation showed that the probability of deriving the global optimal solution of the mission planning algorithm was 96.6% and the computation time was 1.6 s. Furthermore, USV showed it performs the mission according to the results of the MPS. We expect that the MPS developed in this study can be applied to the real environment where USV performs missions with limited time conditions.