As robotic systems evolve toward large-scale distributed architectures and cloud-edge collaboration, communication middleware has become a critical infrastructure that impacts system real-time performance and scalability. The traditional Robot Operating System 1 (ROS 1) communication architecture, which relies on a centralized master node, has limitations in dynamic network environments. Robot Operating System 2 (ROS 2) achieves decentralized communication through the introduction of DDS. However, the single Data Distribution Service (DDS) mechanism remains inadequate for cross-network communication and high-performance local data exchange. Addressing the current issue in ROS communication research: the coexistence of multiple mechanisms without a unified analytical framework or guidance for selection. This paper systematically traces the evolution of the ROS communication architecture from centralized to distributed systems. It constructs a unified analytical framework covering two dimensions: communication models and data transmission paths. Crucially, to overcome the unreliability of cross-protocol comparisons based on heterogeneous literature, this paper designs and executes a set of unified benchmark experiments on a controlled testbed. These experiments systematically evaluate the performance of two mainstream DDS implementations (CycloneDDS and FastDDS) across five key metrics: latency, throughput, jitter, scalability, and packet loss rate under load. Additionally, a comprehensive comparative analysis of the performance of three transmission modes is conducted. Based on this comprehensive evaluation, this paper summarizes the performance characteristics of different mechanisms and further proposes an optimization-based middleware selection method for quantitative communication mechanism selection under different workload and application requirements. This paper provides a systematic reference for the design and optimization of ROS communication systems and offers guidance for promoting the application of multi-middleware collaborative architectures in robotic systems.
Wei et al. (Sun,) studied this question.