dorotos – Tooling Suite for Containerized ROS Applications

docker-ros automatically builds minimal container images of ROS applications

docker-ros-ml-images provides machine learning-enabled ROS base container images

docker-run is a CLI tool for simplified interaction with container images during development

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This repository accompanies our paper on automated containerization for ROS applications. It links to the specific tool repositories that were developed as part of this work.

Enabling the Deployment of Any-Scale Robotic Applications in Microservice Architectures through Automated Containerization
(IEEE Xplore, arXiv, ResearchGate)

Jean-Pierre Busch and Lennart Reiher, Lutz Eckstein
Institute for Automotive Engineering (ika), RWTH Aachen University

^{Abstract – In an increasingly automated world - from warehouse robots to self-driving cars - streamlining the development and deployment process and operations of robotic applications becomes ever more important. Automated DevOps processes and microservice architectures have already proven successful in other domains such as large-scale customer-oriented web services (e.g., Netflix). We recommend to employ similar microservice architectures for the deployment of small- to large-scale robotic applications in order to accelerate development cycles, loosen functional dependence, and improve resiliency and elasticity. In order to facilitate involved DevOps processes, we present and release a tooling suite for automating the development of microservices for robotic applications based on the Robot Operating System (ROS). Our tooling suite covers the automated minimal containerization of ROS applications, a collection of useful machine learning-enabled base container images, as well as a CLI tool for simplified interaction with container images during the development phase. Within the scope of this paper, we embed our tooling suite into the overall context of streamlined robotics deployment and compare it to alternative solutions.}

Acknowledgements

This work is accomplished within the projects 6GEM (FKZ 16KISK036K) and AUTOtech.agil (FKZ 01IS22088A). We acknowledge the financial support for the projects by the Federal Ministry of Education and Research of Germany (BMBF).