MeROS: SysML-based Metamodel for ROS-based Systems
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Abstract (arXiv)
The complexity of today's robot control systems implies difficulty in developing them efficiently and reliably. Systems engineering (SE) and frameworks come to help. The framework metamodels are needed to support the standardisation and correctness of the created application models. Although the use of frameworks is widespread nowadays, for the most popular of them, Robot Operating System (ROS), a contemporary metamodel has been missing so far. This article proposes a new metamodel for ROS called MeROS, which addresses the running system and developer workspace. The ROS comes in two versions: ROS 1 and ROS 2. The metamodel includes both versions. In particular, the latest ROS 1 concepts are considered, such as nodelet, action, and metapackage. An essential addition to the original ROS concepts is the grouping of these concepts, which provides an opportunity to illustrate the system's decomposition and varying degrees of detail in its presentation. The metamodel is derived from the requirements and verified on the practical example of Rico assistive robot. The matter is described in a standardised way in SysML (Systems Modeling Language). Hence, common development tools that support SysML can help develop robot controllers in the spirit of SE.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 14 Mar 2023.
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Citing papers per year: 2024: 4; 2025: 0; 2026: 2.
6 papers.
- 2026Modeling and Recovering Hierarchical Structural Architectures of ROS 2 Systems from Code and Launch Configurations using LLM-based Agentscited by 2
- 2024A comparative analysis of deep learning models for lung segmentation on X-ray imagescited by 0
- 2024Interpreting and learning voice commands with a Large Language Model for a robot systemcited by 0
- 2024Mitigating Dimensionality in 2D Rectangle Packing Problem under Reinforcement Learning Schemacited by 0
- 2024Cartesian Genetic Programming Approach for Designing Convolutional Neural Networkscited by 0
- 2026Towards LLM-Assisted Architecture Recovery for Real-World ROS~2 Systems: An Agent-Based Multi-Level Approach to Hierarchical Structural Architecture Reconstructioncited by 0
- 2026Towards LLM-Assisted Architecture Recovery for Real-World ROS~2 Systems: An Agent-Based Multi-Level Approach to Hierarchical Structural Architecture Reconstruction19 May 2026
- 2026Modeling and Recovering Hierarchical Structural Architectures of ROS 2 Systems from Code and Launch Configurations using LLM-based Agents20 Feb 2026
- 2024Cartesian Genetic Programming Approach for Designing Convolutional Neural Networks30 Sep 2024
- 2024Mitigating Dimensionality in 2D Rectangle Packing Problem under Reinforcement Learning Schema15 Sep 2024
- 2024Interpreting and learning voice commands with a Large Language Model for a robot system31 Jul 2024
- 2024A comparative analysis of deep learning models for lung segmentation on X-ray images9 Apr 2024