Model-Free Trajectory Tracking Control of Two-Particle Magnetic Microrobot

We report a novel model-free trajectory tracking control scheme for two-particle magnetic microrobot (TPMM), which is capable of performing two-dimensional locomotion on a surface in fluid. In the control scheme, the dynamic model of the microrobot and external disturbances are lumped together and treated as the generalized disturbance, which eliminates the complex dynamics modeling of the microrobot due to the hydrodynamics and boundary effect. By employing an extended state observer, the motion states of the microrobot (i.e., position and velocity) are estimated, and the generalized disturbance is compensated. Then, a linear trajectory tracking controller is designed by utilizing the estimated motion states. Furthermore, a visual servoing control system is implemented and extensive real-time trajectory tracking experiments are conducted. The experimental results show the effectiveness of the proposed control scheme for realizing high-precision trajectory tracking for TPMM samples with different body-lengths and surrounding fluids.

[1]  D. Marr,et al.  Surface-enabled propulsion and control of colloidal microwheels , 2016, Nature Communications.

[2]  A. Alexander-Katz,et al.  Controlled surface-induced flows from the motion of self-assembled colloidal walkers , 2009, Proceedings of the National Academy of Sciences.

[3]  Lixin Dong,et al.  Artificial bacterial flagella: Fabrication and magnetic control , 2009 .

[4]  Li Zhang,et al.  A Miniature Flexible-Link Magnetic Swimming Robot With Two Vibration Modes: Design, Modeling and Characterization , 2017, IEEE Robotics and Automation Letters.

[5]  Yuechao Wang,et al.  Applications of Micro/Nano Automation Technology in Detecting Cancer Cells for Personalized Medicine , 2017, IEEE Transactions on Nanotechnology.

[6]  Xiaohui Yan,et al.  Magnetic Actuation Based Motion Control for Microrobots: An Overview , 2015, Micromachines.

[7]  P. Fischer,et al.  Magnetic Propulsion of Microswimmers with DNA-Based Flagellar Bundles , 2016, Nano letters.

[8]  Antoine Ferreira,et al.  Adaptive Controller and Observer for a Magnetic Microrobot , 2013, IEEE Transactions on Robotics.

[9]  Antoine Ferreira,et al.  2D Observer-Based Control of a Vascular Microrobot , 2017, IEEE Transactions on Automatic Control.

[10]  A. Leshansky,et al.  Highly Efficient Freestyle Magnetic Nanoswimmer. , 2017, Nano letters.

[11]  Bradley J. Nelson,et al.  Model Predictive Control of a Magnetically Guided Rolling Microrobot , 2016, IEEE Robotics and Automation Letters.

[12]  Dorin Comaniciu,et al.  Real-time tracking of non-rigid objects using mean shift , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[13]  Vijay Kumar,et al.  Automated biomanipulation of single cells using magnetic microrobots , 2013, Int. J. Robotics Res..

[14]  Ignacio Pagonabarraga,et al.  Controlled swimming in confined fluids of magnetically actuated colloidal rotors. , 2008, Physical review letters.

[15]  A. Agung Julius,et al.  Multiple-robot drug delivery strategy through coordinated teams of microswimmers , 2014 .

[16]  Joseph Wang,et al.  Micro/nanorobots for biomedicine: Delivery, surgery, sensing, and detoxification , 2017, Science Robotics.

[17]  S. Misra,et al.  MagnetoSperm: A microrobot that navigates using weak magnetic fields , 2014 .

[18]  Islam S. M. Khalil,et al.  Disturbance observer-based motion control of paramagnetic microparticles against time-varying flow rates , 2016, 2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob).

[19]  Islam S. M. Khalil,et al.  The Control of Self-Propelled Microjets Inside a Microchannel With Time-Varying Flow Rates , 2014, IEEE Transactions on Robotics.

[20]  Qian Feng,et al.  Magnetite Nanostructured Porous Hollow Helical Microswimmers for Targeted Delivery , 2015 .

[21]  Qi Zhou,et al.  Multifunctional biohybrid magnetite microrobots for imaging-guided therapy , 2017, Science Robotics.