Impact of ROS 2 Node Composition in Robotic Systems

TL;DR

This paper evaluates the performance impact of ROS 2's Component node composition, demonstrating its benefits for resource efficiency and distributed processing in robotic systems through benchmarking experiments.

Contribution

It provides the first comprehensive benchmarking analysis of ROS 2 Component node composition, highlighting its performance advantages in robotic applications.

Findings

Component nodes enable significant performance optimization.

Composition improves resource management in constrained systems.

Benchmark results show enhanced distributed processing capabilities.

Abstract

The Robot Operating System 2 (ROS 2) is the second generation of ROS representing a step forward in the robotic framework. Several new types of nodes and executor models are integral to control where, how, and when information is processed in the computational graph. This paper explores and benchmarks one of these new node types -- the Component node -- which allows nodes to be composed manually or dynamically into processes while retaining separation of concerns in a codebase for distributed development. Composition is shown to achieve a high degree of performance optimization, particularly valuable for resource-constrained systems and sensor processing pipelines, enabling distributed tasks that would not be otherwise possible in ROS 2. In this work, we briefly introduce the significance and design of node composition, then our contribution of benchmarking is provided to analyze its impact on robotic systems. Its compelling influence on performance is shown through several experiments on the latest Long Term Support (LTS) ROS 2 distribution, Humble Hawksbill.