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Adaptive Force Field Research on Plane Arbitrary Training Trajectory of Upper Limb Rehabilitation Robot Based on Admittance Control

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Intelligent Robotics and Applications (ICIRA 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13456))

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Abstract

In order to further improve the flexibility, safety and training pertinence of the desktop end-traction type upper limb rehabilitation robot, this paper proposes a realization method of the adaptive force field of plane arbitrary training trajectory based on admittance control. In ROS, the flexible drag of the robot end is realized through the admittance control algorithm. For the drag trajectory, the function equation is obtained by fitting, and then the desired pose is adjusted in real time through the end pose to realize the trajectory force field. For the regular trajectory force field, a simpler plane segmentation method is used to achieve. The size of the force field is adaptively adjusted by means of position-force control, and the force is compensated in the tangential direction of the desired position, so as to realize the active rehabilitation training of the adaptive force field. The experimental results show that adding an adaptive force field to any plane training trajectory can improve training compliance, safety and training pertinence, which has an important reference for the application of personalized compliance active training to desktop upper limb rehabilitation robots.

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Notes

  1. 1.

    This work was supported in part by the National Natural Science Foundation of China (61903360, 92048302, U20A20197, U1813214), and LiaoNing Revitalization Talents Program (XLYC1908030).

References

  1. Zhou, H., Zhao, J., Li, B.J.: Correlation of peripheral nerve injury to motor function of upper limb in convalescent patients with peripheral paralysis after stroke. Chinese J. Rehabil. Theory Pract. 26(11), 1333–1338 (2020). https://doi.org/10.3969/j.issn.1006-9771.2020.11.015

    Article  Google Scholar 

  2. Gao, P.C., Tang, F.: Effect of intelligent rehabilitation training system on upper limb and hand function of patients with stroke. Chinese J. Rehabil. Theory Pract. 26(10), 1198–1203 (2020). https://doi.org/10.3969/j.issn.1006-9771.2020.10.013

    Article  Google Scholar 

  3. Li, Y.Q., Zeng, Q., Huang, G.Z.: Application of robot-assisted upper limb rehabilitation for stroke (review). Chinese J. Rehabil. Theory Pract. 26(3), 310–314 (2020). https://doi.org/10.3969/j.issn.1006-9771.2020.03.009

  4. Krebs, H.I., Ferraro, M., Buerger, S.P.: Rehabilitation robotics: pilot trial of a spatial extension for MIT-manus. J. Neuroengineering Rehabil. 1(1), 1–15 (2004). https://doi.org/10.1186/1743-0003-1-5

  5. Mihelj, M., Nef, T., Riener, R.: ARMin - Toward a six DoF upper limb rehabilitation robot. In: IEEE/RAS-EMBS International Conference on Biomedical Robotics & Biomechatronics, pp. 1154–1159, BioRob (2022). https://doi.org/10.1109/BIOROB.2006.1639248

  6. Zhang, Z.G.,Wo, Q.C.: Adaptive active interactive training control of upper limb rehabilitation robot based on Barrier Lyapunov function. Instrum. Technol. 5(19), 1–10 (2022). https://kns.cnki.net/kcms/detail/11.2179.TH.20220223.1903.006.html

  7. Le, Y.Q., Guo, S.: Research on compliance control method of upper limb rehabilitation robot based on variable admittance control. Ind. Control Comp. 34(10), 4 (2021). https://doi.org/10.3969/j.issn.1001-182X.2021.10.005

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Correspondence to Dao-Hui Zhang .

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Lin, G., Zhang, DH., Gu, YL., Zhao, XG. (2022). Adaptive Force Field Research on Plane Arbitrary Training Trajectory of Upper Limb Rehabilitation Robot Based on Admittance Control. In: Liu, H., et al. Intelligent Robotics and Applications. ICIRA 2022. Lecture Notes in Computer Science(), vol 13456. Springer, Cham. https://doi.org/10.1007/978-3-031-13822-5_24

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  • DOI: https://doi.org/10.1007/978-3-031-13822-5_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-13821-8

  • Online ISBN: 978-3-031-13822-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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