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Message Passing Optimization in Robot Operating System

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Abstract

With the development of deep learning, autonomous robot systems grow rapidly and require better performance. Robot Operating System 2 (ROS2) has been widely adopted as the main communication framework in autonomous robot systems. However, the performance of ROS2 has become the bottleneck of these real-time systems. From our observations, we find that it can take a large amount of time to serialize complex message in communication, especially for some high-level programming languages, including Python, Java and so on. To address this challenge, we propose a novel technique, called adaptive two-layer serialization algorithm, which can achieve good performance in communication for different kinds of messages. Experimental results show that our algorithm can achieve significant performance improvement over traditional methods in ROS2, up to 93% improvement in our framework. We have successfully applied our proposed techniques in a real autonomous robot system.

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Acknowledgements

We would like to thank the anonymous reviewers for their valuable comments. This work is partially supported by the National Key R&D Program of China (Grant No. 2016YFB0200100), National Natural Science Foundation of China (Grant No. 61722208).

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Authors and Affiliations

  1. Tusimple, Beijing, China

    Ziyue Jiang, Yifan Gong, Wei Liu, Hao Wu & Jiangming Jin

  2. Tsinghua University, Beijing, China

    Jidong Zhai & Yu-Ping Wang

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  1. Ziyue Jiang
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  2. Yifan Gong
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  5. Wei Liu
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Correspondence to Ziyue Jiang.

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Jiang, Z., Gong, Y., Zhai, J. et al. Message Passing Optimization in Robot Operating System. Int J Parallel Prog 48, 119–136 (2020). https://doi.org/10.1007/s10766-019-00647-w

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