提出一种高速无人机编队自主协调控制方法，让编队在极限速度下仍能保持形状。
FF-MPCC: High-speed Agile Formation Flight with Model Predictive Contouring Control
- 将编队维持融入模型预测轮廓控制框架，实现分布式协同
- 在21米/秒高速下形成保持能力提升65%，路径追踪时间相当
- 适用于需要实时变编队形状的复杂轨迹飞行场景
在要求极高的轨迹上以敏捷方式飞行并保持指定编队，仍是无人机领域的一大挑战，尤其在接近平台极限速度时。本文提出一种新的去中心化编队飞行方法，将编队维持整合进模型预测轮廓控制（MPCC）框架，使无人机能在复杂路径上自适应推进，同时遵守个体动态约束并保持期望编队形态。为此，我们引入一种针对动态编队几何的新参数化与同步方法，并设计去中心化策略确定各无人机的目标位置。该方法使编队可在不牺牲编队完整性的前提下实现高速路径跟踪。通过大量仿真和真实实验验证，涵盖不同复杂度路径及实时变更编队形状的场景。相比传统时间参数化轨迹跟踪，在最高21米/秒的速度下，编队保持性能提升65%，且到达目标所需时间相当。
原文摘要 · Abstract (English)
Flying in a prescribed formation in an agile manner remains a challenging problem in the field of UAVs, particularly when following highly-demanding trajectories that require flight at platform limits. We address this problem by proposing a novel decentralized approach to formation flight along a given path that integrates formation maintenance into the MPCC framework, allowing UAVs to adapt their progression along complex paths while respecting individual dynamic constraints and maintaining the desired formation. To this end, we introduce a novel reparametrization and synchronization method for dynamic formation geometries together with a decentralized approach to determine the desired positions for the individual UAVs. The proposed approach allows the formation to coordinate high-speed path following without compromising formation integrity. The proposed approach is validated through extensive simulation and real-world experiments involving scenarios with varying complexity of paths and changes of required formation shape on the fly. In comparison to time-parameterized trajectory tracking, we demonstrate improved formation maintenance by 65% in high-speed flight with velocities up to 21 m/s, while achieving comparable times required to reach the goal.
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