为固定翼恒速飞行器编队的安全且风-aware同步路径规划
Safe and wind-aware synchronous path planning for a fleet of fixed-wing constant speed aircraft
AI总结：
本文提出一种集中式方法，通过枚举不同Dubins路径解决多架固定翼飞行器的同步路径规划问题，确保飞行器间最小分离并维持巡航速度，通过整数线性规划验证全局无冲突解的存在性。
摘要：
多无人飞行器路径规划是一个困难的任务，尤其是对于固定翼飞行器编队而言。一个具体案例是飞行编队的过渡或转换，需要同步到达同时确保最小分离，并理想地维持巡航速度。本文提出了一种基于枚举不同Dubins路径的集中式方法来解决这个问题。给定飞行队列的旅行时间，为每架飞行器构建一组可能的路径。然后，它并行检查每对路径之间的分离。这会产生一个整数线性规划问题的系数，确定是否存在全局无冲突的解决方案。此过程对不同旅行时间进行采样，以增加分辨率，直到达到用户定义的精度。该方法通过考虑多达20架飞行器的蒙特卡洛模拟进行验证，实现了95%的成功率，平均计算时间为8秒。
英文摘要：
Path planning for multiple unmanned aerial vehicles is a difficult task, and even more for a fleet of fixed-wing aircraft. One specific case is the transition to, or between, formation flight patterns, which requires synchronous arrivals while ensuring minimal separation, and ideally maintaining cruise speed. We present a centralized method to solve this problem based on enumerating different Dubins paths. Given a travel time for the fleet, it builds a set of possible paths for each aircraft. Then, it checks in parallel separation between each path pair. This yields coefficients for an Integer Linear Programming problem determining if a fleet-wide conflict-free solution exists. This process is repeated for different travel times sampled with increasing resolution until the user-defined accuracy is met. The method is benchmarked with Monte-Carlo simulations considering up to 20 aircraft simultaneously, achieving an 95% success rate for an average 8 seconds computation time.
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。
