Papers
Topics
Authors
Recent
Search
2000 character limit reached

Service Discovery-Based Hybrid Network Middleware for Efficient Communication in Distributed Robotic Systems

Published 31 Jul 2025 in cs.RO, cs.DC, and cs.NI | (2508.00947v1)

Abstract: Robotic middleware is fundamental to ensuring reliable communication among system components and is crucial for intelligent robotics, autonomous vehicles, and smart manufacturing. However, existing robotic middleware often struggles to meet the diverse communication demands, optimize data transmission efficiency, and maintain scheduling determinism between Orin computing units in large-scale L4 autonomous vehicle deployments. This paper presents RIMAOS2C, a service discovery-based hybrid network communication middleware designed to tackle these challenges. By leveraging multi-level service discovery multicast, RIMAOS2C supports a wide variety of communication modes, including multiple cross-chip Ethernet protocols and PCIe communication capabilities. Its core mechanism, the Message Bridge, optimizes data flow forwarding and employs shared memory for centralized message distribution, reducing message redundancy and minimizing transmission delay uncertainty. Tested on L4 vehicles and Jetson Orin domain controllers, RIMAOS2C leverages TCP-based ZeroMQ to overcome the large-message transmission bottleneck in native CyberRT. In scenarios with two cross-chip subscribers, it eliminates message redundancy and improves large-data transmission efficiency by 36 to 40 percent while reducing callback latency variation by 42 to 906 percent. This research advances the communication capabilities of robotic operating systems and proposes a novel approach to optimizing communication in distributed computing architectures for autonomous driving.

Authors (2)

Summary

No one has generated a summary of this paper yet.

Paper to Video (Beta)

No one has generated a video about this paper yet.

Whiteboard

No one has generated a whiteboard explanation for this paper yet.

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Continue Learning

We haven't generated follow-up questions for this paper yet.

Collections

Sign up for free to add this paper to one or more collections.