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An Adaptive Priority Allocation for Formation UAVs in Complex Context
IEEE Transactions on Aerospace and Electronic Systems ( IF 4.4 ) Pub Date : 2020-10-27 , DOI: 10.1109/taes.2020.3034016
Lihua Zhu , Yu Wang , Zhiqiang Wu

A novel passing priority allocation method, based on the collision avoidance urgency, used for a formation of UAVs in a serried obstacle laden environment, is presented in this article. The method employs the collision cone and the prediction of the collision time to evaluate the urgency of imminent collision of each UAV, so as to establish a primary criterion for the priority allocation. And, the priority update policy is also innovative designed to alleviate burdens on the instability of frequent shifty context. This article exploits the potential field in a cooperative way to plan the path for each UAV, steering the UAVs to a given 3-D position, which combines the adaptive priorities to guide the UAVs passing through the barriers in turn. Numerical simulations and semi-physical experiments in designed outdoor condition are carried out to compare the performance of the proposed adaptive priorities with the regular-used default priorities. The total passing time and the energy cost of the semi-physical tests provide the promising validation in terms of the efficiency and superiority of the proposed method.

中文翻译:

复杂环境下编队无人机的自适应优先分配

本文提出了一种新的基于避碰紧急度的通过优先分配方法,该方法用于在满载有障碍物的环境中形成无人机。该方法利用碰撞锥和碰撞时间的预测来评估每个无人机即将发生碰撞的紧迫性,从而为优先级分配建立主要标准。并且,优先级更新策略也是创新的,旨在减轻频繁变化的环境带来的不稳定负担。本文以协作的方式利用势场来计划每个无人机的路径,将无人机操纵到给定的3D位置,该位置结合了自适应优先级以引导无人机依次穿过障碍物。在设计的室外条件下进行了数值模拟和半物理实验,以比较建议的自适应优先级和常规使用的默认优先级的性能。半物理测试的总通过时间和能源成本为所提方法的效率和优越性提供了有希望的验证。
更新日期:2020-10-27
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