DORA: Dataflow Oriented Robotic Architecture
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arXiv
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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866918337612611584 |
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| author | Zhang, Xiaodong Lv, Baorui Tao, Xavier Wang, Xiong Bao, Jie He, Yong Chen, Yue Yang, Zijiang |
| author_facet | Zhang, Xiaodong Lv, Baorui Tao, Xavier Wang, Xiong Bao, Jie He, Yong Chen, Yue Yang, Zijiang |
| contents | Robotic middleware serves as the foundational infrastructure, enabling complex robotic systems to operate in a coordinated and modular manner. In data-intensive robotic applications, especially in industrial scenarios, communication efficiency directly impact system responsiveness, stability, and overall productivity. However, existing robotic middleware exhibit several limitations: (1) they rely heavily on (de)serialization mechanisms, introducing significant overhead for large-sized data; (2) they lack efficient and flexible support for heterogeneous data sizes, particularly in intra-robot communication and Python-based execution environments. To address these challenges, we propose Dataflow-Oriented Robotic Architecture (DORA) that enables explicit data dependency specification and efficient zero-copy data transmission. We implement the proposed framework as an open-source system and evaluate it through extensive experiments in both simulation and real-world robotic environments. Experimental results demonstrate substantial reductions in latency and CPU overhead compared to state-of-the-art middleware. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_13252 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | DORA: Dataflow Oriented Robotic Architecture Zhang, Xiaodong Lv, Baorui Tao, Xavier Wang, Xiong Bao, Jie He, Yong Chen, Yue Yang, Zijiang Robotics Networking and Internet Architecture Robotic middleware serves as the foundational infrastructure, enabling complex robotic systems to operate in a coordinated and modular manner. In data-intensive robotic applications, especially in industrial scenarios, communication efficiency directly impact system responsiveness, stability, and overall productivity. However, existing robotic middleware exhibit several limitations: (1) they rely heavily on (de)serialization mechanisms, introducing significant overhead for large-sized data; (2) they lack efficient and flexible support for heterogeneous data sizes, particularly in intra-robot communication and Python-based execution environments. To address these challenges, we propose Dataflow-Oriented Robotic Architecture (DORA) that enables explicit data dependency specification and efficient zero-copy data transmission. We implement the proposed framework as an open-source system and evaluate it through extensive experiments in both simulation and real-world robotic environments. Experimental results demonstrate substantial reductions in latency and CPU overhead compared to state-of-the-art middleware. |
| title | DORA: Dataflow Oriented Robotic Architecture |
| topic | Robotics Networking and Internet Architecture |
| url | https://arxiv.org/abs/2602.13252 |