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Research on Human-robot Shared Control of Throat Swab Sampling Robot Based on Intention Estimation

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  • Robot and Applications
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Abstract

With the spread and persistence of COVID-19, pharyngeal swab sampling, is an important link in nucleic acid testing, which is characterized by a high workload and susceptibility to infection. Therefore, it is necessary for medical workers to use medical robots instead of manual site sampling for collaborative sampling. However, the traditional teleoperation has difficulty ensuring the closed-loop performance due to the delay of the actual process, along with the weak control performance; Moreover, a robot cannot accurately plan and track sampling paths due to sensor accuracy and the changes in patient pharyngeal posture. The paper proposes a human-robot shared control strategy based on intention estimation, introducing the human intention as a reference, and the operator and robot work together to solve various significant problems during sampling. The human-robot negotiation based on the method includes the human judgement and perception and the robot into the invasion task. Through, the shared control based on the operator intention estimation, the robot can operate the obstacle avoidance and approach the target contact point remotely. Finally, two kinds of experiments of invasion process of throat swab sampling are implemented: a static target invasive experiment and a dynamic target invasive experiment, aiming at two different sampling conditions. Compared with the robotic independent control sampling, the time consumption in the two experiments is reduced by 34.8% and 41.6%, respectively, and the ultimate target position is basically within the scope of sampling field (where the range of the posterior pharynx wall < 20 mm). Thus, the sampling rate can reach 100%. Compared with independent control sampling by humans, the time consumption of the two experiments is respectively reduced by 15.9% and 42.3% on average, and the target position accuracy and sampling rate are quite close. Experimental results show that the control strategy improves the speed, flexibility, and intelligence of task execution compared to common sampling methods, laying the foundation for low-cost human-robot collaborative sampling.

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Authors and Affiliations

  1. Naval Architecture and Ocean Engineering, Dalian Maritime University, Dalian, 116026, China

    Ying-Long Chen, Fu-Jun Song, Peng-Yu Zhao & Yong-Jun Gong

  2. Jiu-jiang Branch of Tianjin Navigation Instrument Research Institute, Jiujiang, 332007, China

    Heng-Fei Yan

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Correspondence to Ying-Long Chen.

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The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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This research was funded by the National Natural Science Foundation of China (NSFC) under Grant 52275053, in part by Fundamental Research Funds for the Central Universities under Grant 3132023513, National Key Research and Development Program 2021YFC2802403, and Ministry of Industry and Information Technology’s High-Tech Ship Project CBG2N21-2-1.

Ying-Long Chen received his B.Eng. and Ph.D. degrees in mechatronic control engineering from Zhejiang University, Zhejiang, China, in 2008 and 2013, respectively. From 2013 to 2016, he has been a Research Assistant with School of Mechanical Engineering, Zhejiang University. Since 2017, he has been an Assistant Professor with the Naval Architecture and Ocean Engineering, Dalian Maritime University. His research interests include fluid power transmission and control, advanced motion control of mechatronic systems, and robotics.

Fu-Jun Song received his B.Eng. degree and a master’s degree in the Naval Architecture and Ocean Engineering College, Dalian Maritime University, Dalian, China, in 2019 and 2022. Since 2022, he has been a Ph.D. student from School of Aeronautics and Astronautics, Sun Yat-Sen University. His research interests include collaborative robotics and humanrobot shared control.

Heng-Fei Yan received his master’s degree in power and mechanical engineering from Wuhan University in 2011. Now he works in Jiu jiang Branch of Tianjin Navigation Instrument Research Institute. His research interests include fluid machinery and engineering research.

Peng-Yu Zhao received a bachelor’s degree in engineering from Dalian Ocean University in 2019, and is a master’s degree student from the School of Naval Architecture and Ocean Engineering, Dalian Maritime University from 2020 to now. His research interests include collaborative robot technology.

Yong-Jun Gong received his Ph.D. degree in mechatronic control engineering from Zhejiang University, Zhejiang, China, in 2005. Since 2005, he has been a Professor with the Naval Architecture and Ocean Engineering College, Dalian Maritime University. His research interests include fluid power transmission and control, water hydraulics, and underwater tools system.

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Chen, YL., Song, FJ., Yan, HF. et al. Research on Human-robot Shared Control of Throat Swab Sampling Robot Based on Intention Estimation. Int. J. Control Autom. Syst. 22, 661–675 (2024). https://doi.org/10.1007/s12555-022-0728-x

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