Robot-Assisted Automated Manipulation Of Microparticle In Complex Biological Micro-Environment

Rapid advances in biological sciences and nanotechnology have led to the increased requirement of robotics and automation at micro scale.Compared with traditional medical methods and biological research techniques,microscopic robots are characterized with more precise,more stable,more flexible features and design freedom,which enables the abilities to complete tasks and effects that cannot be accomplished by traditional medical technologies.Automated manipulation of cells or nanoparticles in the microenvironment have broad application prospects in biomedical and nanoscience,such as automated cell sorting,cell directed transportation,cell characterization,and targeted cancer therapy,etc.However,most existing methods of manipulation are processed under ideal conditions regardless of-system uncertainties and external disturbances.In practically,microparticles used in biological research are usually manipulated in a complex micro-environment with multifarious uncertainties,such as pulsating blood flow.On the other hand,it is difficult to establish an accurate motion model for cell or complex shape microparticle and there is a certain error in position feedback by sensor.All these have open up new challenges to robotic manipulation of cells or nanoparticles in micro-environmentIn this thesis,disturbance observer based robust control methods are utilized to manipulate microbeads in cancer treatment related investigation.First,a microparticle equipped with optical tweezers is robotically controlled to mimic cell migration in vivo Second,a drug-loaded microparticle is steered in endovascular environment to achieve targeted therapy.This work is demonstrated in the following parts.First,this thesis analyzes the principle that the chemoattractant-loaded microparticle can induce cancer cell migration and utilizes a new strategy for inducing cell migration in vitro.The concentration gradient distribution of the chemoattractant released by the microparticle in the liquid environment was simulated based the diffusion theorem.The distribution curve of the drug concentration along with time and relative distance gained.The use of optical tweezers to manipulate microparticles can change the relative distance between the source and the cell,thereby changing the field distribution of the concentration of the chemoattractants around the cells.The process of using optical tweezer system in vitro as an actuator to guide the movement of cell migration by changing the position of the inducing source is proposed.Further,this thesis studies the cascade system consisting of the optical tweezer,microparticle and cell,and proposes the subsystem models of the interaction between the optical tweezer and microparticle and the interaction between the microparticle and cell,respectively.The external microparticle induced cell migration subsystem model is established based on the diffusion law,which describes the relationship between position of drug-loaded microparticle and movement of cell migration.According to the theory of optics theory,an approximate first order linear model of trapping microparticle by optical trap is established.Finally,the system state equation model with the position of the optical trap as the control variable is established.For the cascade system model of optical tweezer-assisted cell migration,a dual-closed loop control strategy is used to drive the microparticle to proactively control cell migration.The A*algorithm and trajectory smoothing algorithm are used to perform two-dimensional planar trajectory planning for microparticle and cell to avoid collisions with obstacles during motion.For the microparticle-cell outer loop subsystem,a disturbance observer-based active disturbance rejection control(ADRC)algorithm is proposed and used to estimate the real-time location and disturbance signals of the cell in real time.This method can solve the problems of uncertainty in cellular system and measurement noises.The inner optical tweezer and microparticle subsystem uses a feedforward plus proportional-integral control algorithm.The stability of the control algorithm is proven.The simulation and experimental results verify the effectiveness of proposed cell migration control algorithm.Due to the presence of other drug-loaded microparticles in the microenvironment,this thesis proposes an interference clearing mechanism based on traffic rules and a feedforword plus proportional-derivative control algorithm.When other non-target interference microparticles appear in the area of interest,we use optical traps to capture them and limit their motion range,which can effectively reduce the influence of interfering beads on the cell migration process.Finally,the method proposed is simulated and verified by experiment.On the other hand,micron-sized particles capable of advancing in blood vessels have a good application prospect for drug-targeted therapy.This article gives the appropriate navigation path for micro-robots in blood vessels.For the navigation of micro-robots in blood vessels,a breadth-first search(BFS)global planning algorithm is introduced,which can find multiple connected channels from the injection site to the target area based on the prior knowledge of the entire vessel map.Considering the limitation of the vascular network and the propulsion,a trajectory generation algorithm combined with A*and B spline interpolation based on a genetic algorithm is proposed to gain a smooth and energy-optimized local trajectory to minimize energy consumption.Considering the influence of pulsatility and inhomogeneity of blood flows and blood vessel wall in endovascular environnment,this article designs a robust controller combined with sliding mode control(SMC)and backstepping for microrobots.This can simplify the construction of system control design and well handle the nonlinearity of the system.In this thesis,the extended state observer(ESO)is used to accurately estimate the position and velocity of the microrobot,which avoids the real-time measurement of blood flow velocity in complex vessels.In summary,observer-based robust control methods can help solve the related problems of precise manipulation of microparticles in complex micro-environments.The automated cell migration control system designed in this article can guide the cells to migrate to the designated area in the case of unknown complex cellular migration response and the presence of obstacles.This study is not only conducive to the biological research of cell migration,but also a preliminary attempt for application developed based on migration in biomedical engineering.Secondly,the proposed navigation control strategy for intravascular drug-loaded microrobot in this thesis does not depend on the prior knowledge of blood flow velocity distribution,and is still able to drive microrobot along the planned trajectory in the presence of environmental interference and position measurement error.The study not only advances the development of active autonomous therapy based on targeted delivery in the field of biomedicine,but also lays a technical foundation for accurate motion control of large batches of particles in vivo.