This research addresses the challenge of executing multi-UAV survey missions over diverse terrains characterized by varying elevations. The approach integrates advanced two-dimensional ergodic search technique with model predictive control of UAV altitude and velocity. Optimization of altitude and velocity is performed along anticipated UAV ground routes, considering multiple objectives and constraints. This yields a flight regimen tailored to the terrain, as well as the motion and sensing characteristics of the UAVs. The proposed UAV motion control strategy is assessed through simulations of realistic search missions and actual terrain models. Results demonstrate the successful integration of model predictive altitude and velocity control with a two-dimensional potential field-guided ergodic search. Adjusting UAV altitudes to near-ideal levels facilitates the utilization of sensing ranges, thereby enhancing the effectiveness of the search. Furthermore, the control algorithm is capable of real-time computation, encouraging its practical application in real-world scenarios.

翻译：本研究旨在解决在地形起伏多变的多无人机勘测任务执行问题。该方法将先进的二维遍历搜索技术与无人机高度和速度的模型预测控制相结合。沿着预估的无人机地面航迹，综合考虑多重目标与约束条件，对高度与速度进行优化。由此形成适应地形特征及无人机运动与传感特性的飞行方案。通过模拟真实搜索任务和实际地形模型，对所提出的无人机运动控制策略进行了评估。结果表明，模型预测高度与速度控制能够成功集成于二维势场导引的遍历搜索中。将无人机高度调整至接近理想水平，有助于发挥传感范围效能，从而提升搜索效率。此外，该控制算法具备实时计算能力，有利于在实际场景中推广应用。