Distributed Robotic Systems in the Edge-Cloud Continuum with ROS 2: a Review on Novel Architectures and Technology Readiness

Jiaqiang Zhang, Farhad Keramat, Xianjia Yu, Daniel Montero Hernández, J. P. Queralta, Tomi Westerlund
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引用次数: 10

Abstract

Robotic systems are more connected, networked, and distributed than ever. New architectures that comply with the de facto robotics middleware standard, ROS 2, have recently emerged to fill the gap in terms of hybrid systems deployed from edge to cloud. This paper reviews new architectures and technologies that enable containerized robotic applications to seamlessly run at the edge or in the cloud. We also overview systems that include solutions from extension to ROS 2 tooling to the integration of Kubernetes and ROS 2. Another important trend is robot learning, and how new simulators and cloud simulations are enabling, e.g., large-scale reinforcement learning or distributed federated learning solutions. This has also enabled deeper integration of continuous interaction and continuous deployment (CI/CD) pipelines for robotic systems development, going beyond standard software unit tests with simulated tests to build and validate code automatically. We discuss the current technology readiness and list the potential new application scenarios that are becoming available. Finally, we discuss the current challenges in distributed robotic systems and list open research questions in the field.
边缘云连续体中的分布式机器人系统与ROS 2:对新架构和技术准备的回顾
机器人系统比以往任何时候都更加互联、网络化和分布式。符合事实上的机器人中间件标准ROS 2的新架构最近出现,以填补从边缘到云部署的混合系统方面的空白。本文回顾了使容器化机器人应用程序能够在边缘或云中无缝运行的新架构和技术。我们还概述了包括从扩展到ROS 2工具到Kubernetes和ROS 2集成的解决方案的系统。另一个重要的趋势是机器人学习,以及新的模拟器和云模拟如何实现,例如大规模强化学习或分布式联邦学习解决方案。这也使得机器人系统开发的持续交互和持续部署(CI/CD)管道的深度集成成为可能,超越了使用模拟测试的标准软件单元测试,从而自动构建和验证代码。我们将讨论当前的技术准备情况,并列出可用的潜在新应用程序场景。最后,我们讨论了分布式机器人系统当前面临的挑战,并列出了该领域的开放研究问题。
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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