广东工业大学学报 ›› 2023, Vol. 40 ›› Issue (01): 68-76.doi: 10.12052/gdutxb.210120

• • 上一篇    下一篇

一种核磁共振兼容液压驱动穿刺手术机器人的动力学建模及H∞控制方法研究

黄芳, 邱榆富, 郭靖   

  1. 广东工业大学 自动化学院，广东 广州 510006
  • 收稿日期:2021-08-10 出版日期:2023-01-25 发布日期:2023-01-12
  • 通信作者: 郭靖(1986-),男,副教授,博士,主要研究方向为遥操作、手术机器人,E-mail:jing.guo@gdut.edu.cn
  • 作者简介:黄芳(1999-),女,硕士研究生,主要研究方向为手术机器人
  • 基金资助:
    国家自然科学基金青年基金资助项目(61803103)

Dynamic Modeling and H∞ Control Method of an MRI-compatible Hydraulically Needle Insertion Robot

Huang Fang, Qiu Yu-fu, Guo Jing   

  1. School of Automation, Guangdong University of Technology, Guangzhou 510006, China
  • Received:2021-08-10 Online:2023-01-25 Published:2023-01-12

HTML

PDF (PC)

1628

摘要： 脑瘤是影响国民健康状况的重大难题。为了确定脑瘤的发展程度，以确定下一步治疗方案，通常需要对脑瘤组织进行穿刺活检手术。由于核磁共振成像(Magnetic Resonance Imaging, MRI)对软组织有更好的分辨率，常用来检测脑部肿瘤。因此，针对MRI兼容的机器人的相关研究是非常必要的。本文基于一种核磁共振兼容的液压驱动穿刺手术机器人，根据液压连通器的原理，推导了该机器人的运动学模型，并基于流体力学的相关理论，得到了该机器人的动力学模型。为了精确控制所设计的机器人系统，根据H∞控制理论设计了该液压驱动系统的状态反馈H∞控制率，使机器人可以快速、稳定地跟踪目标信号。最后，通过实验研究，该机器人系统的综合定位精度为0.56 mm，在x轴、y轴、z轴、俯仰轴和横滚轴上的平均定位精度分别为0.41 mm、0.6 mm、0.67 mm、0.886°和1.17°。研究结果验证了机器人辅助定位穿刺针的性能，所建立的动力学模型和控制方法对穿刺机器人的控制算法研究有一定的参考价值。

关键词: 核磁共振兼容, 穿刺活检手术, 机器人, H∞控制

Abstract: Brain tumors are a major problem affecting the health status of the nation. To determine the extent of brain tumor in order to determine the next step in treatment, a puncture biopsy procedure of brain tumor tissue is often required. Magnetic resonance imaging (MRI) is commonly used to detect brain tumors due to its better soft-tissue resolution. Therefore, research related to MRI-compatible robots is necessary. Based on an MRI-compatible hydraulically driven puncture surgery robot, the kinematic model of the robot is derived based on the principle of hydraulic linker, and the dynamic model of the robot is obtained based on the relevant theory of fluid dynamics. In order to realize the accurate control of the designed robot system, the state feedback H∞ control rate of this hydraulically driven system is designed according to the H∞ control theory, which enables the robot to track the target signal quickly and stably. Finally, the average positioning accuracy of the designed robot system in x-axis, y-axis, z-axis, pitch-axis and roll-axis are obtained through experimental studies, and they are, respectively, 0.41 mm, 0.6 mm, 0.67 mm, 0.886° and 1.17°. Experimental results verify the performance of robot-assisted positioning puncture needles, and the dynamic model and control method of the robot have been given, which provide certain reference value for the research of the control algorithm of puncture robots.

Key words: MRI-compatible, needle biopsy, robotic system, H∞ control

中图分类号: 

  • TP242
[1] KHIEWVAN B, TORIGIAN D A, EMAMZADEHFARD S, et al. An update on the role of PET/CT and PET/MRI in ovarian cancer [J]. European Journal of Nuclear Medicine & Molecular Imaging, 2017, 44(6): 1079-1091.
[2] MOREIRA P, BOSKMA K J, MISRA S. Towards MRI-guided flexible needle steering using fiber Bragg grating-based tip tracking[C]// 2017 IEEE International Conference on Robotics and Automation (ICRA) . Singapore: IEEE, 2017: 4849-4854.
[3] BALL M W, ROSS A E, GHABILI K, et al. Safety and feasibility of direct magnetic resonance imaging-guided transperineal prostate biopsy using a novel magnetic resonance imaging-safe robotic device [J]. Urology, 2017, 109: 216-221.
[4] ZHANG T X, WEN Y S, LIU Y H. Developing a parallel robot for MRI-guided breast intervention [J]. IEEE Transactions on Medical Robotics and Bionics, 2020, 2(1): 17-27.
[5] GROENHUIS V, SIEPEL F J, VELTMAN J, et al. Design and characterization of Stormram 4: an MRI-compatible robotic system for breast biopsy[C]// 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Vancouver: IEEE, 2017: 928-933.
[6] HE Z, DONG Z, FANG G, et al. Design of a percutaneous MRI-guided needle robot with soft fluid-driven actuator [J]. IEEE Robotics and Automation Letters, 2020, 5(2): 2100-2107.
[7] LI G, NIRAVKUMAR A P, LIU W Q, et al. A fully actuated body-mounted robotic assistant for MRI-guided low back pain injection[C]// 2020 IEEE International Conference on Robotics and Automation (ICRA) . Paris: IEEE, 2020: 5495-5501.
[8] NIRAVKUMAR A P, CHRISTOPHER J N, PAULO A C, et al. An integrated robotic system for MRI-guided neuroablation: preclinical evaluation [J]. IEEE Transactions on Biomedical Engineering, 2020, 67(10): 2990-2999.
[9] GUO Z Y, DONG Z Y, KIT-HANG L, et al. Compact design of a hydraulic driving robot for intra-operative MRI-guided bilateral stereotactic neurosurgery [J]. IEEE Robotics & Automation Letters, 2018, 3(3): 2515-2522.
[10] GYEONG HU K, NIRAVKUMAR P, YAN J W, et al. Shoulder-mounted robot for MRI-guided arthrography: clinically optimized system[C]// 2019 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) . Berlin: IEEE, 2019: 1977-1980.
[11] NIRAVKUMAR A P, YAN J W, DAVID L, et al. Body-mounted robot for image-guided percutaneous interventions: mechanical design and preliminary accuracy evaluation[C]// 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems. Madrid: IEEE, 2018: 1443-1448.
[12] NYCZ C J, GONDOKARYONO R, CARVALHO P, et al. Mechanical validation of an MRI compatible stereotactic neurosurgery robot in preparation for pre-clinical trials[C]// 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) . Vancouver: IEEE, 2017: 875-881.
[13] FRANCO E, BRUJIC D, REA M, et al. Needle-guiding robot for laser ablation of liver tumors under MRI guidance [J]. IEEE/ASME transactions on mechatronics:A joint publication of the IEEE Industrial Electronics Society and the ASME Dynamic Systems and Control Division, 2016, 21(2): 931-944.
[14] DONG Z Y, GUO Z Y, KIT-HANG L, et al. High-performance continuous hydraulic motor for MR safe robotic teleoperation [J]. IEEE Robotics & Automation Letters, 2019, 4(2): 1964-1971.
[15] FARIMANI F S, MISRA S. Introducing pneuact: parametrically-designed MRI-compatible pneumatic stepper actuator[C]// 2018 IEEE International Conference on Robotics and Automation (ICRA) . Brisbane: IEEE, 2018: 4523-4536.
[16] FRISHMAN S, KIGHT A, PIROZZI I, et al. Enabling in-bore MRI-guided biopsies with force feedback [J]. IEEE Transactions on Haptics, 2020, 13(1): 159-166.
[1] 何汉武, 余秋硕, 聂晖, 何明桐, 李晋芳. 基于HTC Vive的虚拟工业机器人示教编程系统[J]. 广东工业大学学报, 2023, 40(02): 30-38.
[2] 邹恒, 高军礼, 张树文, 宋海涛. 围棋机器人落子指引装置的设计与实现[J]. 广东工业大学学报, 2023, 40(01): 77-82,91.
[3] 刘洋, 彭世国, 马宏志, 廖维新. 下肢外骨骼机器人动力学参数辨识与步态跟踪[J]. 广东工业大学学报, 2022, 39(06): 44-52.
[4] 彭积广, 肖涵臻. 模型预测控制下多移动机器人的跟踪与避障[J]. 广东工业大学学报, 2022, 39(05): 93-101.
[5] 王东, 黄瑞元, 李伟政, 黄之峰. 面向抓取任务的移动机器人停靠位置优化方法研究[J]. 广东工业大学学报, 2021, 38(06): 53-61.
[6] 叶培楚, 李东, 章云. 基于双目强约束的直接稀疏视觉里程计[J]. 广东工业大学学报, 2021, 38(04): 65-70.
[7] 揭云飞, 王峰, 钟有东, 智凯旋, 熊超伟. 基于地面特征的单目视觉机器人室内定位方法[J]. 广东工业大学学报, 2020, 37(05): 31-37.
[8] 刘瑞雪, 曾碧, 汪明慧, 卢智亮. 一种基于高效边界探索的机器人自主建图方法[J]. 广东工业大学学报, 2020, 37(05): 38-45.
[9] 叶伟杰, 高军礼, 蒋丰, 郭靖. 一种提升机器人强化学习开发效率的训练模式研究[J]. 广东工业大学学报, 2020, 37(05): 46-50.
[10] 陈宇鹏, 高伟强, 卢一光. 手把手示教喷涂机器人的示教数据优化方法[J]. 广东工业大学学报, 2020, 37(04): 21-26.
[11] 岑仕杰, 何元烈, 陈小聪. 结合注意力与无监督深度学习的单目深度估计[J]. 广东工业大学学报, 2020, 37(04): 35-41.
[12] 刘彪, 黄之峰, 章云. 借助外力助推的双足机器人越障及避障方法研究[J]. 广东工业大学学报, 2019, 36(02): 62-69.
[13] 吴运雄, 曾碧. 基于深度强化学习的移动机器人轨迹跟踪和动态避障[J]. 广东工业大学学报, 2019, 36(01): 42-50.
[14] 汪盛民, 林伟, 曾碧. 未知环境下基于虚拟子目标的对立Q学习机器人路径规划[J]. 广东工业大学学报, 2019, 36(01): 51-56,62.
[15] 梁嘉俊, 曾碧, 何元烈. 基于改进势场栅格法的清洁机器人路径规划算法研究[J]. 广东工业大学学报, 2016, 33(04): 30-36.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
版权所有 © 2017 《广东工业大学学报》编辑部
地址：广州市东风东路729号广东工业大学 邮编：510090
电话：020-37626653,020-37626139,020-37626396
邮箱：xbzrb@gdut.edu.cn
本系统由北京玛格泰克科技发展有限公司设计开发