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ACbot: an IIoT platform for industrial robots

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Abstract

As the application of Industrial Robots (IRs) scales and related participants increase, the demands for intelligent Operation and Maintenance (O&M) and multi-tenant collaboration rise. Traditional methods could no longer cover the requirements, while the Industrial Internet of Things (IIoT) has been considered a promising solution. However, there’s a lack of IIoT platforms dedicated to IR O&M, including IR maintenance, process optimization, and knowledge sharing. In this context, this paper puts forward the multi-tenant-oriented ACbot platform, which attempts to provide the first holistic IIoT-based solution for O&M of IRs. Based on an information model designed for the IR field, ACbot has implemented an application architecture with resource and microservice management across the cloud and multiple edges. On this basis, we develop four vital applications including real-time monitoring, health management, process optimization, and knowledge graph. We have deployed the ACbot platform in real-world scenarios that contain various participants, types of IRs, and processes. To date, ACbot has been accessed by 10 organizations and managed 60 industrial robots, demonstrating that the platform fulfills our expectations. Furthermore, the application results also showcase its robustness, versatility, and adaptability for developing and hosting intelligent robot applications.

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Acknowledgements

This research was supported by the Zhejiang Province Key R&D Program of China (2023C01070).

Author information

Authors and Affiliations

  1. School of Computer Science and Engineering, Beihang University, Beijing, 100191, China

    Rui Wang, Xudong Mou, Yuxin Liu, Tiejun Wang & Xudong Liu

  2. Zhongguancun Laboratory, Beijing, 100194, China

    Xudong Mou, Tianyu Wo & Xudong Liu

  3. School of Software, Beihang University, Beijing, 100191, China

    Tianyu Wo

  4. School of Mechatronics Engineering, Harbin Institute of Technology, Harbin, 150001, China

    Mingyang Zhang & Jihong Yan

  5. Hangzhou Innovation Institute, Beihang University, Hangzhou, 310051, China

    Tiejun Wang & Xudong Liu

  6. School of Information Engineering, China University of Geosciences, Beijing, 100083, China

    Pin Liu

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  1. Rui Wang
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Corresponding author

Correspondence to Tianyu Wo.

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Competing interests The authors declare that they have no competing interests or financial conflicts to disclose.

Additional information

Rui Wang received his MS degree from the School of Mechanical Engineering, Beihang University, China in 2017. He is currently a PhD candidate at the School of Computer Science and Engineering, Beihang University, China. His research interests mainly include cloud computing, IIoT, and time series analysis.

Xudong Mou received her BS and MS degrees in the School of Computer Science and Engineering, Beihang University, China in 2017 and 2021, respectively. She is working towards a PhD degree at the School of Computer Science and Engineering, Beihang University, China. Her research interest is time series anomaly detection.

Tianyu Wo (Member, IEEE) received his BS and PhD degrees in computer science from Beihang University, China in 2001 and 2008, respectively. He is a professor at the College of Software, Beihang University, China. His current research interests include distributed systems and IoT.

Mingyang Zhang received his BE degree from the School of Mechatronics Engineering, Harbin Institute of Technology, China in 2017. Now he is a PhD candidate in the School of Mechatronics Engineering, Harbin Institute of Technology, China. His research interests include IIoT and cloud-based process optimization of industrial robots.

Yuxin Liu received her BS degree from the School of Electronic Information Engineering, Central South University, China in 2019. She received her MS degree at the School of Computer Science, Beihang University, China in 2022. Her research interest is the knowledge graph.

Tiejun Wang received her BS degree from the School of Information Science and Engineering, Shandong Agricultural University, China in 2020. She is currently working towards a PhD degree at the School of Computer Science and Engineering, Beihang University, China. Her research interest is time series analysis.

Pin Liu received his PhD degree from the School of Computer Science and Engineering, Beihang University, China in 2022. Currently, he is a lecturer at the School of Information Engineering, China University of Geosciences (Beijing), China. His research interest is time series data augmentation.

Jihong Yan is a professor and the Deputy Dean of the School of Mechatronics Engineering, Harbin Institute of Technology, China. She has led several National Key R&D Programs and NSFC projects. She has published over 150 papers with more than 2000 citations. Her research interests include intelligent manufacturing, IIoT, and integrated optimal operation of manufacturing systems.

Xudong Liu is a professor at the School of Computer Science and Engineering, Beihang University, China. He has led several China 863 Programs and government projects. He has published over 100 articles. He holds more than 20 patents. His research interests include software middleware technology, software development methods and tools, large-scale information technology projects, and the application of research and teaching.

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Wang, R., Mou, X., Wo, T. et al. ACbot: an IIoT platform for industrial robots. Front. Comput. Sci. 19, 194203 (2025). https://doi.org/10.1007/s11704-024-3449-x

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