一种无人机群编程框架

Dimitris Dedousis, V. Kalogeraki
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引用次数: 7

摘要

近年来,城市环境中的传感系统正在被无人驾驶飞行器(uav)所取代。无人机,也被称为无人驾驶飞机,在执行不同类型的传感任务,如搜索和救援,目标跟踪,检查等方面显示出巨大的潜力。无人机的传感能力和敏捷机动性可以取代现有的复杂解决方案。然而,协调一群无人机完成任务并不是一项微不足道的任务。现有的文献只关注于管理蜂群,而没有提供自动化整个任务的选项。本文提出了一种新的无人机群编程框架——PaROS (PROgramming Swarm)。PaROS提供了一组编程原语,用于编排一群无人机以及自动化某些类型的任务。这些原语,被称为抽象蜂群,控制蜂群中的每一个无人机,从程序员隐藏低级细节的复杂性,如分配飞行计划,任务划分,故障恢复和区域划分。实验验证了该方法的稳定性、时效性和实用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Framework for Programming a Swarm of UAVs
In recent years, sensing systems in urban environments are being replaced by Unmanned Aerial Vehicles (UAVs). UAVs, also known as drones, have shown great potential in executing different kinds of sensing missions, such as search and rescue, object tracking, inspection, etc. The UAVs' sensing capabilities and their agile mobility can replace existing complex solutions for such missions. However, coordinating a swarm of drones for mission accomplishment is not a trivial task. Existing works in the literature focus solely on managing the swarm and do not provide options for automating entire missions. In this paper, we present PaROS (PROgramming Swarm), a novel framework for programming a swarm of UAVs. PaROS provides a set of programming primitives for orchestrating a swarm of drones along with automating certain types of missions. These primitives, referred as abstract swarms, control every drone in the swarm, hiding the complexity of low level details from a programmer such as assigning flight plans, task partitioning, failure recovery and area division. Our experimental evaluation proves that our approach is stable, time-efficient and practical.
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