王景港, 夏光明, 代煜, 张建勋. 基于振动触觉反馈的机器人辅助骨曲面铣削[J]. 机器人, 2021, 43(4): 484-492.DOI: 10.13973/j.cnki.robot.210001.
WANG Jinggang, XIA Guangming, DAI Yu, ZHANG Jianxun. Robot-assisted Milling on the Bone Curved Surface Based on Vibrotactile Feedback. ROBOT, 2021, 43(4): 484-492. DOI: 10.13973/j.cnki.robot.210001.
摘要在骨曲面铣削时,机器人在控制铣削深度的同时需调整刀具与骨面的夹角来确保手术质量.针对这一问题,本文首先建立了铣刀的振动模型,讨论了铣削时铣刀与骨切面的夹角对铣削振动的影响.其次利用固定在铣刀上的三轴加速度传感器,采集铣刀在铣削过程中的振动信号,并使用快速傅里叶变换从信号中提取出铣刀旋转频率谐波的幅值.然后通过先验实验拟合出切向加速度信号中的一次谐波幅值与深度的线性关系,同时得到轴向加速度信号中的一次谐波幅值随夹角变化的关系,证明这两种谐波幅值可作为控制深度和夹角的反馈量.最后利用PID(比例-积分-微分)控制器和机器人逆运动学提出了基于振动触觉的骨曲面铣削方法.实验结果表明,铣削深度设置值为0.5 mm时,未引入和引入夹角控制方法时的骨曲面铣削深度的均值和标准差分别为0.455 mm ±0.046 mm和0.499 mm ±0.028 mm.所提方法能提高机器人铣削骨曲面的精确度.
Abstract:When milling on the bone curved surface, a robot needs to adjust the angle between the tool and the bone surface while controlling the milling depth to ensure the quality of the operation. For this problem, the vibration model of milling cutter is established firstly, and the influence of the angle between the cutter and the bone surface on milling vibration is discussed. Secondly, the three-axis acceleration sensor fixed on the cutter is used to collect the cutter vibration signals during the milling process, and the fast Fourier transform is used to extract the harmonic amplitude of the cutter rotation frequency. Thirdly, the linear relationship between the amplitude of the first harmonic in the tangential acceleration signal and the depth is fitted through a priori experiment, and the relationship between the amplitude of the first harmonic in the axial acceleration signal and the angle is obtained. It is proved that these two harmonics can be used as the feedback for controlling the milling depth and its angle. Finally, the bone curved surface milling method based on vibration tactile sensation is proposed based on PID (proportional-integral-differential) controller and robot inverse kinematics. Experimental results show that when the milling depth is set to 0.5 mm, the average and standard deviation of the milling depth on the bone curved surface before and after the angle control are 0.455 mm ±0.046 mm and 0.499 mm ±0.028 mm. The proposed method can improve the robot-assisted milling accuracy on the bone curved surface.
[1] 王震, 宋晓菲, 陈彤云.临床外科手术中骨切削技术的研究现状及进展[J].工程科学学报, 2019, 41(6):709-718. Wang Z, Song X F, Chen T Y. A review of bone cutting in surgery[J]. Chinese Journal of Engineering, 2019, 41(6): 709-718. [2] Dai Y, Xue Y, Zhang J X.Bioinspired integration of auditory and haptic perception in bone milling surgery[J]. IEEE/ASME Transactions on Mechatronics, 2018, 32(2): 614-623. [3] 王天然.机器人技术的发展[J].机器人, 2017, 39(4):385-386. Wang T R. Development of the robotics[J]. Robot, 2017, 39(4): 385-386. [4] Fan L P, Gao P, Zhao B L, et al.Safety control strategy for vertebral lamina milling task[J]. CAAI Transactions on Intelligence Technology, 2016, 1(3): 249-258. [5] Gierlak P.Hybrid position/force control in robotised machining[J]. Solid State Phenomena, 2014, 210: 192-199. [6] Deng Z, Jin H Y, Hu Y, et al.Fuzzy force control and state detection in vertebral lamina milling[J]. Mechatronics, 2016, 35: 1-10. [7] Dillon N P, Fichera L, Wellborn P S, et al.Making robots mill bone more like human surgeons: Using bone density and anatomic information to mill safely and efficiently[C]//IEEE/ RSJ International Conference on Intelligent Robots and Sys-tems. Piscataway, USA: IEEE, 2016: 1837-1843. [8] Sun Y, Jiang Z L, Qi X Z, et al.Robot-assisted decompressive laminectomy planning based on 3D medical image[J]. IEEE Access, 2018, 6: 22557-22569. [9] 代煜, 雪原, 张建勋.基于声信号处理的骨铣削状态监测[J].振动与冲击, 2015, 34(22):19-23. Dai Y, Xue Y, Zhang J X, et al. Bone milling condition monitoring based on sound signal processing[J]. Journal of Vibration and Shock, 2015, 34(22): 19-23. [10] Sun Y, Jin H Y, Hu Y, et al.State recognition of bone drilling with audio signal in robotic orthopedics surgery system[C]// IEEE/RSJ International Conference on Intelligent Robots and Systems. Piscataway, USA: 2014: 3503-3508. [11] 夏光明, 代煜, 张建勋, 等.一种基于声信号的手术机器人骨切削深度控制方法[J].机器人, 2021, 43(1):101-111. Xia G M, Dai Y, Zhang J X, et al. A method of bone cutting depth control for surgical robot based on acoustic signals[J]. Robot, 2021, 43(1): 101-111. [12] Zakeri V, Hodgson A J.Automatic identification of hard and soft bone tissues by analyzing drilling sounds[J]. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2019, 27(2): 404-414. [13] Dai Y, Xue Y, Zhang J X.Condition monitoring based on sound feature extraction during bone drilling process[C]//33rd Chinese Control Conference. Piscataway, USA: IEEE, 2014: 7317-7322. [14] Dai Y, Xue Y, Zhang J X.Bioinspired integration of auditory and haptic perception in bone milling surgery[J]. IEEE/ASME Transactions on Mechatronics, 2018, 23(2): 614-623. [15] Dai Y, Xue Y, Zhang J X.Estimation of tool position based on vibration sense during robotic bone milling[C]//IEEE International Conference on Robotics and Biomimetics. Piscataway, USA: IEEE, 2016: 57-61. [16] Dai Y, Xue Y, Zhang J X.Milling state identification based on vibration sense of a robotic surgical system[J]. IEEE Transactions on Industrial Electronics, 2016, 63(10): 6184-6193. [17] 陈启森, 刘宇, 石秋香.球头铣刀骨铣削力有限元建模与试验验证[J].工具技术, 2020, 54(5):12-17. Chen Q S, Liu Y, Shi Q X. Finite element modeling and experimental verification of bone milling force using spherical milling cutter[J]. Tool Engineering, 2020, 54(5): 12-17. [18] 代煜, 贾宾, 张建勋, 等.基于振动反馈的铣削机器人运动控制[J].天津大学学报(自然科学与工程技术版), 2020, 53(10):1093-1100. Dai Y, Jia B, Zhang J X, et al. Motion control of milling robot based on vibration feedback[J]. Journal of Tianjin University (Science and Technology), 2020, 53(10): 1093-1100. [19] 宋国立, 韩冰, 赵忆文, 等.脊柱微创手术机器人速度场控制方法[J].机器人, 2016, 38(5):603-611. Song G L, Han B, Zhao Y W, et al. Velocity field control method of a minimally invasive spine surgical robot[J]. Robot, 2016, 38(5): 603-611. [20] Jayaram S, Kapoor S G, DeVor R E.Estimation of the specific cutting pressures for mechanistic cutting force models[J]. International Journal of Machine Tools & Manufacture, 2001, 41(2): 265-281. [21] Jiang Z L, Qi X Z, Sun Y, et al.Cutting depth monitoring based on milling force for robot-assisted laminectomy[J]. IEEE Transactions on Automation Science and Engineering, 2020, 17(1): 2-14.