鲁棒分布式协同路径跟随与局部重计划用于不同低空路径的多UAVs
Robust Distributed Cooperative Path-Following and Local Replanning for Multi-UAVs Under Differentiated Low-Altitude Paths
AI总结：
本文提出了一种鲁棒分布式协同路径跟随与局部重计划方法，解决多UAVs在复杂地形低空环境下面对风场扰动、突发障碍和分布式时间同步的挑战，通过时间索引量化问题，结合鲁棒引导法则实现风扰下的有限时间稳定，设计高效局部路径重计划方法以实现实时避障。
摘要：
多固定翼无人机（多UAVs）在复杂数字高程模型（DEM）低空空域中进行协同路径跟随面临显著挑战，包括风场扰动、突发障碍和不同路径跟踪时的分布式时间同步要求。现有方法缺乏有效的时间一致跟踪3D不同路径的分布式协调机制，无法量化对扰动的鲁棒性，且缺乏有效的在线障碍避让重计划能力。为解决这些不足，提出了一种协同控制策略：首先，通过时间索引量化分布式协同路径跟随问题，并通过分布式通信协议确保一致性；其次，开发了一种纵向-横向前瞻角度调整方法，结合鲁棒引导法则，以在风扰下实现路径跟随误差在有限时间内稳定至零；第三，设计了一种高效局部路径重计划方法，具有最小的时间成本，用于实时在线障碍避让。实验验证展示了所提策略的有效性和优越性。
英文摘要：
Multiple fixed-wing unmanned aerial vehicles (multi-UAVs) encounter significant challenges in cooperative path following over complex Digital Elevation Model (DEM) low-altitude airspace, including wind field disturbances, sudden obstacles, and requirements of distributed temporal synchronization during differentiated path tracking. Existing methods lack efficient distributed coordination mechanisms for time-consistent tracking of 3D differentiated paths, fail to quantify robustness against disturbances, and lack effective online obstacle avoidance replanning capabilities. To address these gaps, a cooperative control strategy is proposed: first, the distributed cooperative path-following problem is quantified via time indices, and consistency is ensured through a distributed communication protocol; second, a longitudinal-lateral look-ahead angle adjustment method coupled with a robust guidance law is developed to achieve finite-time stabilization of path following error to zero under wind disturbances; third, an efficient local path replanning method with minimal time cost is designed for real-time online obstacle avoidance.Experimental validations demonstrate the effectiveness and superiority of the $\ $proposed strategy.
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