Multiple UAVs trajectory generation and waypoint assignment in urban environment based on DOP maps

Causa Flavia; Fasano Giancarmine

摘要

This paper tackles strategic path planning for a multi-UAV routing problem in low altitude urban environment, where GNSS coverage challenges typically affect navigation performance and thus autonomous flight capabilities. These issues are addressed with a multi-step strategy that includes automated definition of GNSS-challenging volumes based on a georeferenced three-dimensional environment model, derivation of candidate obstacle-free paths between waypoints, waypoint assignment and definition of time-tagged trajectories for all UAVs. In all the steps, attention is paid to limiting the computational burden, thus ensuring applicability in real mission scenarios. Going beyond binary logics which consider GNSS-challenging volumes as obstacles, a discrete number of dilution of precision levels is considered, leading to different three-dimensional maps of the environment defined as "DOP layers". Then, the basic idea to ensure that the designed trajectories are "flyable" with given positioning accuracy requirements is to take navigation performance into account at waypoint assignment level, using propagated covariance as a metric. The approach thus combines "navigation aware" planning with multi-vehicle task assignment, generating a solution that depends on the sensors embarked onboard the UAVs, and can be naturally extended to account for multi-sensor-based navigation architectures and ground-infrastructure support. The algorithm is tested in simulations based on a real world scenario, considering a wide combination of input parameters in terms of positioning error threshold, maximum UAV velocity, number of UAVs, navigation sensors performance, and mission epoch. (C) 2021 Published by Elsevier Masson SAS.

机译：本文解决了低海拔城市环境中多UAV路由问题的战略路径规划，其中GNSS覆盖挑战通常会影响导航性能，从而影响自主飞行能力。这些问题是通过多步策略解决的，包括基于地理学三维环境模型的GNSS挑战卷的自动定义，候选航点之间的候选障碍路径的推导，所有标记的轨迹的定义无人机。在所有步骤中，关注限制计算负担，从而确保了实际使命方案的适用性。超越二进制逻辑，考虑GNSS - 挑战卷作为障碍，考虑了离散次数的精度稀释，导致环境的不同三维图定义为“DOP层”。然后，基本思想确保设计的轨迹是“Flyable”，具有定位精度要求是在WayPoint分配级别考虑导航性能，使用传播的协方差作为指标。因此，该方法将“导航感知”规划与多车辆任务分配组合，生成取决于传感器的解决方案，该解决方案已经开始了无人机，并且可以自然地扩展以考虑基于多传感器的导航架构和地基基础设施支持。该算法基于真实世界场景在仿真中进行了测试，考虑到在定位误差阈值，最大UAV速度，无人机，导航传感器性能和任务时期的定位误差阈值，最大UAV速度。（c）由Elsevier Masson SA发表的2021年。

Multiple UAVs trajectory generation and waypoint assignment in urban environment based on DOP maps

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