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首页> 外文期刊>Mechatronics, IEEE/ASME Transactions on >Formation Reconstruction and Trajectory Replanning for Multi-UAV Patrol
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Formation Reconstruction and Trajectory Replanning for Multi-UAV Patrol

机译：多UAV巡逻的形成重建与轨迹重新划分

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摘要

This article addresses the dynamic formation reconstruction and trajectory replanning problem in the air patrol task using multiple fixed-wing unmanned aerial vehicle formations. Unlike most of the formation flying related work, this article considers a more practical issue that some of the vehicles may break down during operation. In this case, a more reasonable coping strategy is proposed which is to reconstruct the formation such that the task objectives can be achieved optimally. To perform the patrol task, a virtual target is introduced which moves along the patrol path with a predetermined speed. Considering the fact that not all the vehicles have access to the patrol path information, a decentralized estimator is designed for each vehicle to estimate the virtual target state respectively based on which the individual reference trajectories can be generated. As these reference trajectories do not satisfy relevant physical constraints, including system model, control input limits, no-fly zone avoidance, and intervehicle collision avoidance, a novel model predictive trajectory replanning algorithm is developed to generate feasible reference trajectories for each vehicle in real time, which is computationally attractive by incorporating a situation-dependent mechanism. Simulations have been conducted to validate the effectiveness of our proposed algorithm.
机译：本文通过多个固定翼无人空中车辆结构解决了空中巡逻任务中的动态形成重建和轨迹重新恢复问题。与大多数形成相关的工作不同，本文考虑了一个更实际的问题，即一些车辆在运营期间可能会分解。在这种情况下，提出了更合理的应对策略，该策略是重建形成，使得可以最佳地实现任务目标。为了执行巡逻任务，引入虚拟目标，其沿着具有预定速度的巡逻路径移动。考虑到并非所有车辆具有访问巡逻路径信息的事实，分散的估计器被设计用于每个车辆，以分别基于可以生成各个参考轨迹的虚拟目标状态。由于这些参考轨迹不满足相关的物理限制，包括系统模型，控制输入限制，无飞区域避免和互动冲突避免，开发了一种新型模型预测轨迹重新替换算法，以实时为每个车辆产生可行的参考轨迹，通过结合依赖的机制来计算地具有吸引力。已经进行了仿真以验证我们所提出的算法的有效性。

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