The DOI matches its Crossref record.
Exploring the performance of ROS2
Open accessAbstract
Middleware for robotics development must meet demanding requirements in real-time distributed embedded systems. The Robot Operating System (ROS), open-source middleware, has been widely used for robotics applications. However, the ROS is not suitable for real-time embedded systems because it does not satisfy real-time requirements and only runs on a few OSs. To address this problem, ROS1 will undergo a significant upgrade to ROS2 by utilizing the Data Distribution Service (DDS). DDS is suitable for real-time distributed embedded systems due to its various transport configurations (e.g., deadline and fault-tolerance) and scalability. ROS2 must convert data for DDS and abstract DDS from its users; however, this incurs additional overhead, which is examined in this study. Transport latencies between ROS2 nodes vary depending on the use cases, data size, configurations, and DDS vendors. We conduct proof of concept for DDS approach to ROS and arrange DDS characteristic and guidelines from various evaluations. By highlighting the DDS capabilities, we explore and evaluate the potential and constraints of DDS and ROS2.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
The Marathon 2: A Navigation System
Macenski, S., Martin, F., White, R., & Clavero, J. G. (2020) · 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros45743.2020.9341207 · Cited by 389
Collaborative Multi-Robot Systems for Search and Rescue: Coordination and Perception
Queralta, J. P., Taipalmaa, J., Pullinen, B. C., Sarker, V. K., Gia, T. N., Tenhunen, H., Gabbouj, M., Raitoharju, J., & Westerlund, T. (2020) · arXiv · doi:10.48550/arxiv.2008.12610 · Cited by 27
Metadata
- Authors
- Maruyama, Y., Kato, S., & Azumi, T.
- Venue
- Proceedings of the 13th International Conference on Embedded Software
- Publisher
- ACM
- Published
- 2016-10
- Pages
- 1-10
- OpenAlex
- W2530771494
- Cited by
- 384
- References
- 0
- FWCI
- 22.37
- Type
- conference paper
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Exploring the performance of ROS2. https://app.cochat.ai/papers/10.1145/2968478.2968502
- The paper
- Maruyama, Y., Kato, S., & Azumi, T. (2016). Exploring the performance of ROS2. Proceedings of the 13th International Conference on Embedded Software. https://doi.org/10.1145/2968478.2968502
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
