磁性微纳机器人的制备和运动研究

  微生物为了适应复杂多变的生活环境，进化出了各自独特的运动方式，科研人员从这些微生物身上获取了灵感，提出了微纳机器人这一概念。由于其体积小、质量轻，具有灵活运动、精准靶向、药物运输等能力，相较于传统的宏观机器人，微纳机器人更有望成为应用于疾病诊断、微创手术等生物医学领域的首选方案。然而在眼部手术、心血管介入等复杂微创手术中，微纳机器人所需要完成的体内任务越来越复杂，对微纳机器人结构、材料和运动控制等方面都提出了更高的要求：微纳机器人必须具有更小的尺度、更复杂的结构；微纳机器人需要更高精度的控制方式。针对上述两个关键问题，本课题围绕微纳机器人的设计、制备和运动控制三个方面展开了深入研究。

  本课题通过双光子光刻、物理气相沉积等技术，大批量、可控化地制备出了磁性螺旋管型微纳机器人，该微纳机器人的尺度在微米级别、具有三维复杂螺旋管状结构，表面以铁（Ferrum, Fe）和钛（Titanium, Ti）作为磁性材料和生物相容材料。针对磁性微纳机器人的运动机理和磁驱动方式，在本课题中自主搭建了一套具有友好人机交互性的微纳机器人磁控平台，该平台包括磁场硬件系统和控制软件系统两大板块组成。该磁控平台实现了振荡、旋转、锥形等多种磁场的生成，并预留自定义接口，可针对不同微纳机器人设计出不同的磁场驱动方案。

  针对磁性微纳机器人的精准运动控制，本课题基于检测速度快、轻便的YOLOv5算法框架训练新模型对螺旋管型微纳机器人进行快速精准检测，并利用自主搭建的磁控平台对磁性螺旋管型微纳机器人进行了运动姿态控制并测试了其运动性能，在8 mT磁场驱动下，实现了534 μm/s的螺旋推进运动速度。结合目标检测算法，本课题提出了一种微纳机器人的自动化操作方案，实现了螺旋管型微纳机器人的自主导航，并完成了自动微粒捕获实验，对于将微纳机器人从实验室研究走向实际医学应用迈出了关键一步。

[1] BINGHAM B, FOLEY B, SINGH H, et al. Robotic tools for deep water archaeology: Surveying an ancient shipwreck with an autonomous underwater vehicle[J]. Journal of Field Robotics, 2010, 27(6): 702-717.
[2] 谭民, 王硕. 机器人技术研究进展[J]. 自动化学报, 2013, 39(07): 963-972.
[3] KULAKOV F M. Remote control of space robots[J]. Journal of Computer and Systems Sciences International, 2016, 55: 635- 682.
[4] LUO M, FENG Y Z, WANG T W, et al. Micro-/nanorobots at work in active drug delivery[J]. Advanced Functional Materials, 2018, 28(25): 1706100.
[5] DING J, VENKATESAN R, ZHAI Z H, et al. Micro- and nanoparticles-based immunoregulation of macrophages for tissue repair and regeneration[J]. Colloids and Surfaces B: Biointerfaces, 2020, 192: 111075.
[6] WEI F N, ZHONG T L, ZHAN Z H, et al. Self-assembled micronanorobots: From assembly mechanisms to applications[J]. Chemnanomat, 2021, 7(3): 238-252.
[7] WU S D, RIOS R, MEEKS J, et al. Rectal Hem-o-Lok clip migration after robot-assisted laparoscopic radical prostatectomy[J]. The Canadian Journal of Urology, 2009, 16(6): 4939-4940.
[8] ZHANG L, ABBOTT J, DONG L X, et al. Artificial bacterial flagella: Fabrication and magnetic control[J]. Applied Physics Letters, 2009, 94(6): 064107.
[9] WANG H, PUMERA M. Micro/Nanomachines and Living Biosystems: From Simple Interactions to Microcyborgs[J]. Advanced Functional Materials, 2018, 28(25):1705421.
[10] FEYNMAN R. There’s plenty of room at the bottom[J]. Resonance, 2011, 16(9): 890-905.
[11] 李劲草, 孙岚, 姜爽, 等. 纳米药物释放系统在肿瘤组织中增强的透过与滞留效应及其影响因素[J]. 中国药理学与毒理学杂志, 2015, 29(1): 164-169.
[12] CHEN X, JANG B, AHMED D, et al. Small-scale machines driven by external power sources[J]. Advanced Materials, 2018, 30(15): 1705061.
[13] 谭力源. 基于旋转磁场的简单形状微纳机器人制造及其游泳性能分析[D]. 哈尔滨: 哈尔滨工业大学机械工程学科硕士学位论文, 2019. DOI: 10.27061/d.cnki.ghgdu.2019.002413.
[14] HONDA T, ARAI K, ISHIYAMA K. Micro swimming mechanisms propelled by external magnetic fields[J]. IEEE Transactions on Magnetics, 1996, 32(5): 5085-5087.
[15] DREYFUS R, BAUDRY J, ROPER M L, et al. Microscopic Artificial Swimmers[J]. Nature, 2005, 437(7060): 862-865.
[16] LUO M, FENG Y, WANG T, et al. Micro-Nanorobots at Work in Active Drug Delivery[J]. Advanced Functional Materials, 2018, 28(25): 17-23.
[17] JIN D D, YU J F, HUANG T Y, et al. Magnetic micro-/nanoscale swimmers: Current status and potential applications[J]. Chinese Science Bulletin, 2017, 62(2/3): 136-151.
[18] PATIL G, GHOSH A. Anomalous behavior of highly active helical swimmers[J]. Frontiers in Physics, 2021, 8: 628276.
[19] ALSAADAWI Y, EICHLER-VOLF A, HEIGL M, et al. Control over self assembled Janus clusters by the strength of magnetic field in H2O2[J]. The European Physical Journal E, 2021, 44: 1-8.
[20] LIN Z H, FAN X J, SUN M M, et al. Magnetically actuated peanut colloid motors for cell manipulation and patterning[J]. ACS Nano, 2018, 12(3): 2539-2545.
[21] MENG F L, MATSUNAGA D, GOLESTANIAN R. Clustering of magnetic swimmers in a poiseuille flow[J]. Physical Review Letters, 2018, 120(18): 188101.
[22] VILFAN M, OSTERMAN N, VILFAN A. Magnetically driven omnidirectional artificial microswimmers[J]. Soft Matter, 2018, 14(17): 3415-3422.
[23] OULMAS A, ANDREFF N, REGNIER S. 3D closed-loop swimming at low Reynolds numbers[J]. International Journal of Robotics Research, 2018, 37(11): 1359-1375.
[24] HUANG T Y, SAKAR M S, MAO A, et al. 3D Printed Microtransporters: Compound Micromachines for Spatiotemporally Controlled Delivery of Therapeutic Agents[J]. Advanced Materials, 2015, 27(42): 6644-6650.
[25] KADIRI V M, BUSSI C, HOLLE A W, et al. Biocompatible magnetic micro- and nanodevices: Fabrication of FePt nanopropellers and cell transfection[J]. Advanced Materials, 2020, 32(25): 2001114.
[26] YANG L, CHEN X X, WANG L, et al. Targeted single-cell therapeutics with magnetic tubular micromotor by one-step exposure of structured femtosecond optical vortices[J]. Advanced Functional Materials, 2019, 29(45): 1905745.
[27] ALAPAN Y, BOZUYUK U, ERKOC P, et al. Multifunctional surface microrollers for targeted cargo delivery in physiological blood flow[J]. Science Robotics, 2020, 5(42): eaba5726.
[28] LIU Z Y, XU T T, WANG M, et al. Magnetic mesoporouads silica/εpolylysine nanomotor-based removers of blood Pb2+[J]. Journal of Materials Chemistry B, 2020, 8(48): 11055-11062.
[29] ZHANG Y B, ZHANG L, YANG L D, et al. Real-time tracking of fluorescent magnetic spore–based microrobots for remote detection of C.diff toxins[J]. Science Advances, 2019, 5(1): eaau9650.
[30] WU Z G, CHEN Y, MUKASA D, et al. Medical micro/nanorobots in complex media[J]. Chemical Society Reviews, 2020, 49 (22): 8088-8112.
[31] WU Z G, TROLL J, JEONG H H, et al. A swarm of slippery micropropellers penetrates the vitreous body of the eye[J]. Science Advances, 2018, 4(11): eaat4388.
[32] ZHONG D N, LI W L, QI Y C, et al. Photosynthetic biohybrid nanoswimmers system to alleviate tumor hypoxia for FL/PA/MR imaging-guided enhanced radio-photodynamic synergetic therapy[J]. Advanced Functional Materials, 2020, 30(17): 1910395.
[33] YAN X H, ZHOU Q, VINCENT M, et al. Multifunctional biohybrid magnetite microrobots for imaging-guided therapy[J]. Science Robotics, 2017, 2(12): eaaq1155.
[34] YASA I C, CEYLAN H, BOZUYUK U, et al. Elucidating the interaction dynamics between microswimmer body and immune system for medical microrobots[J]. Science Robotics, 2020, 5(43): eaaz3867.
[35] CABANACH P, PENA-FRANCESCH A, SHEEHAN D, et al. Zwitterionic 3D-printed non-immunogenic stealth microrobots[J]. Advanced Materials, 2020, 32(42): 202003013.
[36] YU J F, WANG B, DU X Z, et al. Ultra-extensible ribbon-like magnetic microswarm[J]. Nature Communications, 2018, 9(1): 3260.
[37] YU J F, JIN D D, CHAN K F, et al. Active generation and magnetic actuation of microrobotic swarms in bio-fluids[J]. Nature Communications, 2019, 10(1): 5631.
[38] DONG X G, SITTI M. Controlling two-dimensional collective formation and cooperative behavior of magnetic microrobot swarms[J]. International Journal of Robotics Research, 2020, 39(5): 617-638.
[39] XIE H, SUN M M, FAN X J, et al. Reconfigurable magnetic microrobot swarm: Multimode transformation, locomotion, and manipulation[J]. Science Robotics, 2019, 4(28): eaav8006.
[40] MA W, NIU F, LI X, et al. Automated manipulation of magnetic micro beads with electromagnetic coil system[C]//IEEE International Conference on Nano/molecular Medicine and Engineering. IEEE, 2013: 47-50.
[41] GUAN Y, XU T, JIA L, et al. Image-based visual servoing of helical microswimmers for arbitrary planar path following at low reynolds numbers[C]//2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2017: 1883-1888.
[42] BERGELES C, KRATOCHVIL B E, NELSON B J. Visually Servoing Magnetic Intraocular Microdevices[J]. IEEE Transactions on Robotics, 2012, 28(4):798-809.
[43] RYAN P, DILLER E. Magnetic Actuation for Full Dexterity Microrobotic Control Using Rotating Permanent Magnets[J]. IEEE Transactions on Robotics, 2017, 33(6):1398-1409.
[44] ARCESE. L, FRUCHARD, et al. Adaptive Controller and Observer for a Magnetic Microrobot Gradient Coils of a magnetic device[J]. IEEE Transactions on Robotics, 2013, 29(4):1060-1067.
[45] ARCESE L, CHERRY A, FRUCHARD M, et al. High Gain Observer for Backstepping Control of a MRI-guided Therapeutic Microrobot in Blood Vessels[C]//IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics. IEEE, 2010: 349-354.
[46] ARCESE L, FRUCHARD M, FERREIRA A. Nonlinear Modeling and Robust Controller-Observer for a Magnetic Microrobot in a Fluidic Environment using MRI gradients[C]//IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE, 2009: 534-539.
[47] DILLER E, JIANG Z, GUO Z L, et al. Continuously distributed magnetization profile for millimeter-scale elastomeric undulatory swimming[J]. Journal of Applied Physics, 2014, 115(17):174101.1-174101.4.
[48] XIE H, FAN X, SUN M, et al. Programmable Generation and Motion Control of a Snakelike Magnetic Microrobot Swarm[J]. IEEE/ASME Transactions on Mechatronics, 2019, 24(3): 902-912.
[49] LI T, CHANG X, WU Z, et al. Autonomous Collision-Free Navigation of Micro vehicles in Complex and Dynamically Changing Environments[J]. ACS Nano, 2017, 11(9): 9268-9275.
[50] FAN X, SUN M, LIN Z, et al. Automated Noncontact Micromanipulation Using Magnetic Swimming Microrobots[J]. IEEE Transactions on Nanotechnology, 2018, 17(4): 666-669.
[51] BELHARET K, FOLIO D, FERREIRA A. Endovascular navigation of a ferromagnetic microrobot using MRI-based predictive control[C]//IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE, 2010: 2804-2809.
[52] FOLIO D, FERREIRA A. Two-Dimensional Robust Magnetic Resonance Navigation of a Ferromagnetic Microrobot Using Pareto Optimality[J]. IEEE Transactions on Robotics, 2017, 33(3): 583-593.
[53] KIM H, CHEANG U K, ROGOWSKI L W, et al. Motion planning of particle based microrobots for static obstacle avoidance[J]. Journal of Micro-Nano Mechatronics, 2018, 14: 41-49.
[54] 张鹏松, 樊启高, 于振中. 基于视觉反馈的磁性微型机器人自主导航控制[J]. 传感器与微系统, 2021, 40(06): 11-15.
[55] LIU J, XU T T, YANG S X, et al. Navigation and Visual Feedback Control for Magnetically Driven Helical Miniature Swimmers[J]. IEEE Transactions on Industrial Informatics, 2019, 16(1): 477-487.
[56] ZHANG L, ABBOTT JJ, DONG L, et al. Artificial bacterial flagella：Fabrication and magnetic control[J]. Applied Physics Letters, 2009, 94(6): 064107.
[57] YU Y, SHANG L, GAO W, et al. Microfluidic Lithography of Bioinspired Helical Micromotors.[J]. Angewandte Chemie, 2017, 129(40): 12295-12299.
[58] WANG X, QIN X H, HU C, et al. 3D Printed Enzymatically Biodegradable Soft Helical Microswimmers[J]. Advanced Functional Materials, 2018, 28(45): 1804107
[59] 刘石. 钛金属医用植入物表面含硒功能涂层的制备及生物学性能研究[D]. 天津: 河北工业大学材料工程学科硕士学位论文, 2022. DOI:10.27105 /d.cnki.ghbgu.2022.000072.
[60] PEYER K E, ZHANG L, NELSON B J. Bio-Inspired Magnetic Swimming Microrobots for Biomedical Applications[J]. Nanoscale, 2013, 5(4):1259-1272.
[61] PURCELL E M. The efficiency of propulsion by a rotating flagellum.[J]. Proceedings of the National Academy of Sciences of the United States of America, 1997, 94(21): 11307-11311.
[62] ABBOTT J J, PEYER K E, LAGOMARSINO M C, et al. How Should Microrobots Swim?[J]. The International Journal of Robotics Research, 2009, 28(11-12): 1434-1447.
[63] 邢金峰. 蒽醌和蒽衍生物双光子聚合引发剂的合成与性能研究[D]. 北京: 中国科学院理化技术研究所有机化学学科博士学位论文, 2007.
[64] WU S, SERBIN J, GU M. Two-photon polymerisation for three-dimensional micro-fabrication[J]. Journal of Photochemistry and Photobiology A: Chemistry, 2006, 181(1): 1-11.
[65] 张慧, 王坤峰, 王飞跃. 深度学习在目标视觉检测中的应用进展与展望[J]. 自动化学报, 2017, 43(8): 1289-1305.
[66] GIRSHICK R, DONAHUE J, DARRELL T, et al. Rich feature hierarchies for accurate object detection and semantic segmentation[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2014: 580-587.
[67] REN S, HE K, GIRSHICK R, et al. Faster R-CNN: Towards real-time object detection with region proposal networks[J]. Advances in Neural Information Processing Systems, 2015, 28.
[68] JIANG P, ERGU D, LIU F, et al. A Review of Yolo Algorithm Developments[J]. Procedia Computer Science, 2022, 199: 1066-1073.
[69] LAN W, DANG J, WANG Y, et al. Pedestrian detection based on YOLO network model[C]//2018 IEEE International Conference on Mechatronics and Automation. IEEE, 2018: 1547-1551.
[70] 裴嘉欣, 孙韶媛, 王宇岚, 等. 基于改进YOLOv3网络的无人车夜间环境感知[J]. 应用光学，2019，40(03): 380-386.
[71] REDMON J, DIVVALA S, GIRSHICK R, et al. You only look once: Unified, real-time object detection[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2016: 779-788.
[72] WANG C Y, LIAO H Y M, WU Y H, et al. CSPNet: A new backbone that can enhance learning capability of CNN[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops. 2020: 390-391.
[73] LIU S, QI L, QIN H, et al. Path aggregation network for instance segmentation[C]// Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2018: 8759-8768.
[74] ZHENG Z, WANG P, LIU W, et al. Distance-IoU loss: Faster and better learning for bounding box regression[C]//Proceedings of the AAAI Conference on Artificial Intelligence. 2020, 34(07): 12993-13000.
[75] WANG L, XU H, ZHAI W. et al. Design and characterization of magnetically actuated helical swimmers at submillimeter-scale[J]. Journal of Bionic Engineering, 2017, 14(1): 26-33.
[76] SHI M, YANG H, LIAO X, et al. Research on strategy of intelligent disinfection robot based on distributed constraint optimization[C]//IEEE International Conference on Artificial Intelligence and Computer Applications. 2021: 82-85.
[77] BUNDY A, WALLEN L. Breadth-first search[J]. Catalogue of Artificial Intelligence Tools, 1984: 13-13.
[78] TARJAN R. Depth-first search and linear graph algorithms[J]. SIAM Journal on Computing, 1972, 1(2): 146-160.
[79] HART P E, NILSSON N J, RAPHAEL B. A formal basis for the heuristic determination of minimum cost paths[J]. IEEE Transactions on Systems Science and Cybernetics, 1968, 4(2): 100-107.
[80] AMATO N M, WU Y. A randomized roadmap method for path and manipulation planning[C]//Proceedings of IEEE International Conference on Robotics and Automation. IEEE, 1996, 1: 113-120.
[81] LAVALLE S M, KUFFNER J J. Rapidly-exploring random trees: Progress and prospects[J]. Algorithmic and Computational Robotics, 2001: 303-307.
[82] 李进文, 何素梅, 吴海彬. 一种直线插补算法及其在机器人中的应用研究[J]. 机电工程, 2015, 32(7): 966-970.
[83] 周虹. 圆弧插补算法的探讨[J]. 机械制造与自动化, 2006, 35(3): 43-44.
[84] 王峰, 王爱玲. B 样条曲线的插补算法实现[J]. 华北工学院学报, 2001, 22(6): 449-452.