Optimizing ROS 2 Communication for Wireless Robotic Systems
🤖 AI Summary
ROS 2 exhibits severe performance degradation when transmitting high-bandwidth payloads—such as high-resolution images and LiDAR point clouds—over wireless networks, primarily due to DDS’s default configuration inducing IP fragmentation, inefficient retransmission, and buffer bursts on lossy links.
Method: This paper presents the first systematic analysis of ROS 2’s DDS stack behavior under wireless conditions and proposes a lightweight, fully compatible QoS adaptation framework. It requires no protocol or source-code modifications; instead, it dynamically tunes XML-defined DDS QoS parameters—including reliability policy, history depth, and send queue length—in response to real-time link-state and payload characteristics to avoid IP fragmentation and optimize retransmission timing.
Contribution/Results: Evaluated across diverse real-world wireless scenarios, the approach enables stable, low-latency end-to-end transmission of large payloads, significantly improving reliability and timeliness without compromising ROS 2 compatibility.
Application Category
📝 Abstract
Wireless transmission of large payloads, such as high-resolution images and LiDAR point clouds, is a major bottleneck in ROS 2, the leading open-source robotics middleware. The default Data Distribution Service (DDS) communication stack in ROS 2 exhibits significant performance degradation over lossy wireless links. Despite the widespread use of ROS 2, the underlying causes of these wireless communication challenges remain unexplored. In this paper, we present the first in-depth network-layer analysis of ROS 2's DDS stack under wireless conditions with large payloads. We identify the following three key issues: excessive IP fragmentation, inefficient retransmission timing, and congestive buffer bursts. To address these issues, we propose a lightweight and fully compatible DDS optimization framework that tunes communication parameters based on link and payload characteristics. Our solution can be seamlessly applied through the standard ROS 2 application interface via simple XML-based QoS configuration, requiring no protocol modifications, no additional components, and virtually no integration efforts. Extensive experiments across various wireless scenarios demonstrate that our framework successfully delivers large payloads in conditions where existing DDS modes fail, while maintaining low end-to-end latency.
Problem
Research questions and friction points this paper is trying to address.
ROS 2 wireless performance degradation with large payloads
Excessive IP fragmentation and inefficient retransmission timing
Congestive buffer bursts in ROS 2 DDS stack
Innovation
Methods, ideas, or system contributions that make the work stand out.
Optimizes ROS 2 DDS for wireless large payloads
Lightweight XML-based QoS tuning framework
Fixes IP fragmentation and retransmission issues
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