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MISSION-ADAPTABLE ROUTE PLANNING IN UNCERTAIN AND ADVERSARIAL ENVIRONMENT

机译:不确定和逆境环境下的任务自适应路线规划

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In this paper, the route-planning problems of Unmanned Aerial Vehicle (UAV) in uncertain and adversarial environment are addressed, including not only single-mission route planning in known a priori environment, but also the route replanning in partially known and mission-changeable environments. A mission-adaptable hybrid route-planning algorithm based on flight roadmap is proposed, which combines existing global and local methods (Dijkstra algorithm, SAS and D{sup}*) into a two-level framework. The environment information and constraints for UAV are integrated into the procedure of building flight roadmap and searching for routes. The route-planning algorithm utilizes domain-specific knowledge and operates in real time with near-optimal solution quality, which is important to uncertain and adversarial environment. Other planners do not provide all of the functionality, namely real-time planning and replanning, near-optimal solution quality, and the ability to model complex 3D constraints.
机译:本文研究了不确定和对抗环境下的无人机航路规划问题,不仅包括已知先验环境下的单任务航路规划,还包括部分已知且任务可改变的航路规划环境。提出了一种基于飞行路线图的任务自适应混合路径规划算法,该算法将现有的全局和局部方法(Dijkstra算法,SAS和D {sup} *)组合成两级框架。无人机的环境信息和约束条件已整合到制定飞行路线图和搜索路线的过程中。路线规划算法利用特定领域的知识并以接近最佳的解决方案质量实时运行,这对于不确定和对抗的环境非常重要。其他计划人员没有提供所有功能,即实时计划和重新计划,接近最佳的解决方案质量以及对复杂3D约束进行建模的能力。

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