Demo abstract: Simbeeotic: A simulation-emulation platform for large scale micro-aerial swarms

J. Waterman, Bryan Kate, Karthik Dantu, M. Welsh
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引用次数: 3

Abstract

Micro-aerial vehicle (MAV) swarms are an emerging class of mobile sensing systems. Designing the next generation of such swarms requires the ability to rapidly test algorithms, sensors, and support infrastructure at scale. Simulation is useful in the early stages of such large-scale system design, when hardware is unavailable or deployment at scale is im-practical. To faithfully represent the problem domain, an MAV swarm simulator must be able to model all key aspects of the system: actuation, sensing, and communication. Further, it is important to be able to quickly test swarm behavior using different control algorithms in a varied set of environments, and with a variety of sensors. We demonstrate Simbeeotic, a simulation framework that is capable of modeling large-scale MAV swarms. Simbeeotic enables algorithm development and rapid prototyping through both simulation and hardware-in-the-loop experimentation. We demonstrate Simbeeotic running simulated applications and videos demonstrating hybrid experiments with simulated MAV s as well as helicopters flying in our test bed that show the power and versatility required to assist next generation swarm design.
摘要:Simbeeotic:大型微型空中蜂群的仿真仿真平台
微型飞行器(MAV)群是一类新兴的移动传感系统。设计下一代这样的集群需要快速测试算法、传感器和大规模支持基础设施的能力。在这种大规模系统设计的早期阶段,当硬件不可用或大规模部署不切实际时,模拟是有用的。为了忠实地表示问题域,MAV群模拟器必须能够模拟系统的所有关键方面:驱动、传感和通信。此外,能够在不同的环境和各种传感器中使用不同的控制算法快速测试群体行为是很重要的。我们展示了Simbeeotic,一个能够模拟大规模MAV群的仿真框架。Simbeeotic通过仿真和硬件在环实验实现算法开发和快速原型设计。我们演示了Simbeeotic运行模拟应用程序和视频,演示了模拟MAV的混合实验,以及在我们的测试平台上飞行的直升机,展示了辅助下一代蜂群设计所需的功率和多功能性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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