多无人机协同巡检风力发电机，用逻辑约束生成安全路径并动态调整。
Task Coordination and Trajectory Optimization for Multi-Aerial Systems via Signal Temporal Logic: A Wind Turbine Inspection Study
- 基于信号时序逻辑构建任务与轨迹优化模型，确保时间与飞行限制合规。
- 仿真与实地实验验证有效，可应对突发延迟并减少任务冲突。
- 适合需要高可靠性巡检的工业场景，如风电、电力设施维护。
本文提出一种多旋翼无人机群在协同巡检任务中的任务分配与轨迹生成方法，聚焦风力发电机巡检应用。通过基于信号时序逻辑（STL）规范构建优化问题，生成满足时间敏感性约束和飞行器性能限制的安全可行路径。引入事件触发式重规划机制以应对突发情况和延误，并采用广义鲁棒性评分方法融合用户偏好、降低任务冲突。该方法在MATLAB和Gazebo中进行仿真验证，并在模拟场景中开展实地实验，结果表明其具备良好的实用性与适应性。
原文摘要 · Abstract (English)
This paper presents a method for task allocation and trajectory generation in cooperative inspection missions using a fleet of multirotor drones, with a focus on wind turbine inspection. The approach generates safe, feasible flight paths that adhere to time-sensitive constraints and vehicle limitations by formulating an optimization problem based on Signal Temporal Logic (STL) specifications. An event-triggered replanning mechanism addresses unexpected events and delays, while a generalized robustness scoring method incorporates user preferences and minimizes task conflicts. The approach is validated through simulations in MATLAB and Gazebo, as well as field experiments in a mock-up scenario.
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