A well-planned dive trajectory is the key for the trans-media maneuver and flight control of morphing unmanned aerial-underwater vehicles (MUAUVs). The main focus of this paper is the application of a watch-based multi-objective grey wolf optimizer (MOGWO) to dive trajectory optimization problems. A multi-objective trajectory optimization model considering the change of sweep angle and static moment is developed and parameterized by the Gauss pseudospectral method, and a multi-objective nonlinear programming problem is constructed. To overcome the defect that, in the MOGWO, the rest wolves blindly follow the best wolves, the watch strategy is introduced, which provides the wolves with the ability of independent exploration. Subsequently, the watch-based MOGWO is employed to generate the Pareto front, which is compared with that obtained through other multi-objective techniques. The simulation results demonstrated that the proposed method is more reliable and can obtain more widely distributed non-dominated solutions, indicating that the watch-based MOGWO is effective and feasible in dealing with multi-objective trajectory optimization problems with complex constraints. In addition, comparative studies on optimal trajectories demonstrated that the maneuverability and gliding ability of the MUAUV are improved through cooperation between the angle-of-attack, bank angle, and sweep angle.

精心规划的潜水轨迹是变型无人机的跨媒体操纵和飞行控制的关键。本文的主要重点是基于手表的多目标灰太狼优化器（MOGWO）的应用，以解决轨迹优化问题。利用高斯伪谱方法建立了考虑后掠角和静力矩变化的多目标轨迹优化模型，并对其进行了参数化，建立了多目标非线性规划问题。为了克服MOGWO中其余狼盲目跟随最佳狼的缺陷，引入了监视策略，这为狼提供了独立探索的能力。随后，使用基于手表的MOGWO生成帕累托锋，与通过其他多目标技术获得的结果进行比较。仿真结果表明，该方法更可靠，可以得到分布更广的非支配解，这表明基于手表的MOGWO在处理复杂约束的多目标轨迹优化问题上是有效和可行的。此外，对最佳轨迹的比较研究表明，MUAUV的机动性和滑行能力通过攻角，倾斜角和后掠角之间的配合得以改善。表明基于手表的MOGWO在处理具有复杂约束的多目标轨迹优化问题方面是有效和可行的。此外，对最佳轨迹的比较研究表明，MUAUV的机动性和滑行能力通过攻角，倾斜角和后掠角之间的配合得以改善。表明基于手表的MOGWO在处理具有复杂约束的多目标轨迹优化问题方面是有效和可行的。此外，对最佳轨迹的比较研究表明，MUAUV的机动性和滑行能力通过攻角，倾斜角和后掠角之间的配合得以改善。