Poster: How to Send Large Data in ROS 2

High-resolution data streams-such as images, Li-DAR point-clouds-are common in robotic communication, yet Robot Operating System 2 (ROS 2) struggles to transmit these streams due to increased average latency. On lossy wireless links, the default DDS communication stack in ROS 2 suffers significant performance degradation. This paper presents the first comprehensive network-layer analysis of ROS 2’s DDS stack operating over wireless links with large payloads. We analyze three network bottlenecks that emerge during large-payload data transfers and presents DDS-level optimizations for each one. The proposed solutions are exposed through an XML-based QoS configuration interface, allowing them to be easily tuned. Experiments demonstrate that our approach transmits large-payload data successfully while maintaining lower latency than existing methods.

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Publication Details

Published
2025-09-22
DOI
https://doi.org/10.1109/icnp65844.2025.11192433
Primary Topic
Distributed and Parallel Computing Systems
Type
article
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article

Poster: How to Send Large Data in ROS 2

Kyung‐Joon Park, Sanghoon Lee, Tae Hun Kim, Jiyeong Chae
Distributed and Parallel Computing Systems
article

Poster: How to Send Large Data in ROS 2

Kyung‐Joon Park, Sanghoon Lee, Tae Hun Kim, Jiyeong Chae
article en

Abstract

High-resolution data streams-such as images, Li-DAR point-clouds-are common in robotic communication, yet Robot Operating System 2 (ROS 2) struggles to transmit these streams due to increased average latency. On lossy wireless links, the default DDS communication stack in ROS 2 suffers significant performance degradation. This paper presents the first comprehensive network-layer analysis of ROS 2’s DDS stack operating over wireless links with large payloads. We analyze three network bottlenecks that emerge during large-payload data transfers and presents DDS-level optimizations for each one. The proposed solutions are exposed through an XML-based QoS configuration interface, allowing them to be easily tuned. Experiments demonstrate that our approach transmits large-payload data successfully while maintaining lower latency than existing methods.

Daegu Gyeongbuk Institute of Science and Technology (KR)
Openalex Percentile: Top 66%
Distributed and Parallel Computing Systems
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Poster: How to Send Large Data in ROS 2 — Kyung‐Joon Park, Sanghoon Lee, et al. · (2025) | TGRS Research Map | TGRS