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.

本研究包含开发可应用于实际情况的 USV 任务规划系统 (MPS) 并通过 HILS 对其进行验证的过程。在这项研究中，我们设置了一个操作时间有限的单个 USV 的场景。由于操作时间有限，USV 可能无法执行某些任务，因此定义了一个目标函数以最大化任务完成率 (MAR)。我们使用遗传算法来解决问题模型，并提出了一种使用 3-D 种群的方法。仿真表明，任务规划算法的全局最优解的推导概率为96.6%，计算时间为1.6 s。此外，USV 表明它根据 MPS 的结果执行任务。