论文标题
在严重环境中的异质地面自动驾驶汽车网络：在DARPA地下挑战赛中的网格网络实施
Heterogeneous Ground-Air Autonomous Vehicle Networking in Austere Environments: Practical Implementation of a Mesh Network in the DARPA Subterranean Challenge
论文作者
论文摘要
在现实生活中实现无线网络网络需要大量的系统工程工作，以将网络概念变成完整的系统。本文对DARPA地下（Subt）挑战最终事件中的现场系统进行了评估，该系统有助于第三名。我们的系统包括一组空气和地面机器人，可部署的网状扩展节点以及人类操作员基站。本文在实用的系统设计局限性下，对在RF有限的环境中对空气和地面机器人勘探进行了优化的堆栈进行了现实评估。我们高度可定制的解决方案利用了最少的非免费组件，这些组件具有适用于无人机操作的外形选项，并洞悉各个级别的网络操作。我们根据我们在DARPA地下挑战的最后事件中的表现介绍了绩效指标，证明了我们方法的实际成功和局限性，以及一系列学习的经验教训和未来改进的建议。
Implementing a wireless mesh network in a real-life scenario requires a significant systems engineering effort to turn a network concept into a complete system. This paper presents an evaluation of a fielded system within the DARPA Subterranean (SubT) Challenge Final Event that contributed to a 3rd place finish. Our system included a team of air and ground robots, deployable mesh extender nodes, and a human operator base station. This paper presents a real-world evaluation of a stack optimized for air and ground robotic exploration in a RF-limited environment under practical system design limitations. Our highly customizable solution utilizes a minimum of non-free components with form factor options suited for UAV operations and provides insight into network operations at all levels. We present performance metrics based on our performance in the Final Event of the DARPA Subterranean Challenge, demonstrating the practical successes and limitations of our approach, as well as a set of lessons learned and suggestions for future improvements.
