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HyperGraph ROS: An Open-Source Robot Operating System for Hybrid Parallel Computing based on Computational HyperGraph
Shufang Zhang, Jiazheng Wu, Jiacheng He, Kaiyi Wang, Shan An
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This paper presents HyperGraph ROS, an open-source robot operating system that unifies intra-process, inter-process, and cross-device computation into a computational hypergraph for efficient message passing and parallel execution. In order to optimize communication, HyperGraph ROS dynamically selects the optimal communication mechanism while maintaining a consistent API. For intra-process messages, Intel-TBB Flow Graph is used with C++ pointer passing, which ensures zero memory copying and instant delivery. Meanwhile, inter-process and cross-device communication seamlessly switch to ZeroMQ. When a node receives a message from any source, it is immediately activated and scheduled for parallel execution by Intel-TBB. The computational hypergraph consists of nodes represented by TBB flow graph nodes and edges formed by TBB pointer-based connections for intra-process communication, as well as ZeroMQ links for inter-process and cross-device communication. This structure enables seamless distributed parallelism. Additionally, HyperGraph ROS provides ROS-like utilities such as a parameter server, a coordinate transformation tree, and visualization tools. Evaluation in diverse robotic scenarios demonstrates significantly higher transmission and throughput efficiency compared to ROS 2. Our work is available at https://github.com/wujiazheng2020a/hyper_graph_ros.
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