🤖 AI Summary
This work addresses the limitations of existing robotic middleware—such as ROS 2—whose architectural complexity, poor interoperability, and steep learning curve hinder the development of efficient cross-platform robotic systems. To overcome these challenges, we propose Meta-ROS, a lightweight middleware architecture built upon modern communication protocols like Zenoh and ZeroMQ. Meta-ROS streamlines integration, supports multimodal data transmission—including audio and video—and enables seamless cross-platform deployment. Experimental results demonstrate that Meta-ROS achieves up to 30% higher throughput, lower message latency, and reduced resource consumption compared to ROS 2, thereby providing a highly compatible, low-latency foundation for real-time robotic AI applications.
📝 Abstract
The field of robotics faces significant challenges related to the complexity and interoperability of existing middleware frameworks, like ROS2, which can be difficult for new developers to adopt. To address these issues, we propose Meta-ROS, a novel middleware solution designed to streamline robotics development by simplifying integration, enhancing performance, and ensuring cross-platform compatibility. Meta-ROS leverages modern communication protocols, such as Zenoh and ZeroMQ, to enable efficient and low-latency communication across diverse hardware platforms, while also supporting various data types like audio, images, and video. We evaluated Meta-ROS's performance through comprehensive testing, comparing it with existing middleware frameworks like ROS1 and ROS2. The results demonstrated that Meta-ROS outperforms ROS2, achieving up to 30% higher throughput, significantly reducing message latency, and optimizing resource usage. Additionally, its robust hardware support and developer-centric design facilitate seamless integration and ease of use, positioning Meta-ROS as an ideal solution for modern, real-time robotics AI applications.