编配
计算机科学
云计算
机器人
分布式计算
模块化(生物学)
嵌入式系统
软件部署
容器(类型理论)
领域(数学分析)
背景(考古学)
软件工程
人工智能
操作系统
工程类
数学分析
艺术
生物
古生物学
视觉艺术
机械工程
音乐剧
遗传学
数学
作者
Francesco Lumpp,Marco Panato,Franco Fummi,Nicola Bombieri
标识
DOI:10.1109/fdl53530.2021.9568376
摘要
Programming modern Robots' missions and behavior has become a very challenging task. The always increasing level of autonomy of such platforms requires the integration of multi-domain software applications to implement artificial intelligence, cognition, and human-robot/robot-robot interaction applications. In addition, to satisfy both functional and nonfunctional requirements such as reliability and energy efficiency, robotic SW applications have to be properly developed to take advantage of heterogeneous (Edge-Fog-Cloud) architectures. In this context, containerization and orchestration are becoming a standard practice as they allow for better information flow among different network levels as well as increased modularity in the use of software components. Nevertheless, the adoption of such a practice along the design flow, from simulation to the deployment of complex robotic applications by addressing the de-facto development standards (i.e., robotic operating system - ROS - compliancy for robotic applications) is still an open problem. We present a design methodology based on Docker and Kubernetes that enables containerization and orchestration of ROS-based robotic SW applications for heterogeneous and hierarchical HW architectures. The design methodology allows for (i) integration and verification of multi-domain components since early in the design flow, (ii) task-to-container mapping techniques to guarantee minimum overhead in terms of performance and memory footprint, and (iii) multi-domain verification of functional and non-functional constraints before deployment. We present the results obtained in a real case of study, in which the design methodology has been applied to program the mission of a Robotnik RB-Kairos mobile robot in an industrial agile production chain. The source code of the mobile robot is publicly available on GitHub.
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