Adaptive Variables for Declarative UAV Planning
Adaptive Variables for Declarative UAV Planning
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DOI：
10.1145/3422584.3422763
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发表时间：
2020-07
期刊：
影响因子：
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通讯作者：
John Henry Burns;Xiaozhou Liang;Yu David Liu
中科院分区：
文献类型：
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作者：
John Henry Burns;Xiaozhou Liang;Yu David Liu
无人机 (UAV) 是自主机器人技术的重要子集，为商品交付、地理调查和灾难恢复等领域提供了独特的机会。无人机的规划层由高层指令组成，指示系统如何实现计划目标。无人机在物理环境中执行其计划，因此计划必须适应动态环境的变化。在本文中，我们提出了一个简单的编程抽象，即自适应变量，以声明性地定义动态上下文中无人机飞行计划的自适应。建立在用于表达无人机飞行计划的声明性语言之上，自适应变量可以在无人机飞行期间根据物理数据的谓词而改变。我们为狗仔队实现了自适应变量，并通过 NPS 模拟器展示了其在自适应无人机规划中的有用性。
Unmanned Aerial Vehicles (UAVs) are an important subset of autonomous robotics, offering unique opportunities in domains like merchandise delivery, geographical survey, and disaster recovery. The planning layer of UAVs is made up of high-level directives that instruct the system on how to achieve the plan's goals. UAVs execute their plans in the physical environment, and thus the plans must adapt to changes in the dynamic context. In this paper, we present a simple programming abstraction, adaptive variables, to declaratively define adaptation for UAV flight plans in a dynamic context. Building on top of a declarative language for expressing UAV flight plans, adaptive variables can change during a UAV flight based on predicates over physical data. We implement adaptive variable for Paparazzi and demonstrate its usefulness in adaptive UAV planning with the NPS Simulator.