基于信号时序逻辑的多无人机系统任务协调与轨迹优化：一项风力涡轮机检测研究
Task Coordination and Trajectory Optimization for Multi-Aerial Systems via Signal Temporal Logic: A Wind Turbine Inspection Study
AI总结：
针对多旋翼无人机协同风力涡轮机检测，提出基于STL规范的任务分配与轨迹优化方法，并结合事件触发重规划和广义鲁棒性评分，经仿真与实地实验验证。
摘要：
本文提出了一种在协同检测任务中进行任务分配与轨迹生成的方法，该方法使用一组多旋翼无人机，重点关注风力涡轮机检测。该方法通过构建基于信号时序逻辑（STL）规范的优化问题，生成满足时间敏感约束和飞行器限制的安全、可行飞行路径。事件触发的重规划机制用于处理意外事件和延误，而广义鲁棒性评分方法则纳入用户偏好并最大限度地减少任务冲突。该方法通过 MATLAB 和 Gazebo 仿真以及样机场景中的实地实验得到了验证。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
