Coordinating movement within swarms of UAVs through mobile networks

B. J. O. D. Souza, M. Endler
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引用次数: 29

Abstract

Unmanned Aerial Vehicles (UAV) have several uses in civilians and military applications, such as search and rescue missions, cartography and terrain exploration, industrial plant control, surveillance, public security, firefight, and others. Swarms of UAVs may further increase the effectiveness of these tasks, since they enable larger coverage, more accurate or redundant sensed data, fault tolerance, etc. Swarms of aerial robots require real-time coordination, which is just a specific case of M2M collaboration. But one of the biggest challenges of UAV swarming is that this real-time coordination has to happen in a wide-area setting where it is expensive, or even impossible, to set up a dedicated wireless infrastructure for this purpose. Instead, one has to resort to conventional 3G/4G wireless networks, where communication latencies are in the range of 50-150 ms. In this paper we tackle the problem of UAV swarm formation and maintenance in areas covered by such mobile network, and propose a bandwidth-efficient multi-robot coordination algorithm for these settings. The coordination algorithm was implemented on the top of our mobile middleware SDDL, uses its group-cast communication capability, and was tested with simulated UAVs.
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通过移动网络协调无人机群内的运动
无人驾驶飞行器(UAV)在民用和军事应用中有几种用途,例如搜索和救援任务、制图和地形勘探、工业工厂控制、监视、公共安全、消防和其他。无人机群可以进一步提高这些任务的有效性,因为它们可以实现更大的覆盖范围,更准确或冗余的感测数据,容错性等。成群的空中机器人需要实时协调,这只是M2M协作的一个具体例子。但无人机群最大的挑战之一是,这种实时协调必须发生在广域环境中,在这种环境中,为此目的建立专用的无线基础设施是昂贵的,甚至是不可能的。相反,人们不得不求助于传统的3G/4G无线网络,其通信延迟在50-150毫秒之间。本文针对此类移动网络覆盖区域的无人机群形成和维护问题,提出了一种带宽高效的多机器人协调算法。该协调算法在移动中间件SDDL上实现,利用其组播通信能力,并在模拟无人机上进行了测试。
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