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Accurate modulation of photoprinting under stiffness imaging feedback for engineering ECMs with high-fidelity mechanical properties

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Microsystems & Nanoengineering 2022年第3期8卷 291-301页

作者： Xin Li Huaping Wang Xinyi Dong Qing Shi Tao Sun Shingo Shimoda Qiang Huang Toshio Fukuda Intelligent Robotics Institute School of Mechatronical EngineeringBeijing Institute of TechnologyBeijing 100081China The Key Laboratory of Biomimetic Robots and Systems(Beijing Institute of Technology) Ministry of EducationBeijing 100081China School of Medical Technology Beijing Institute of TechnologyBeijing 100081China Intelligent Behavior Control Collaboration Unit RIKEN Center of Brain Science463-0003 NagoyaJapan

Engineered extracellular matrices(ECMs)that replicate complex in-vivo features have shown great potential in tissue *** hydrogel microstructures have been widely used to replace these native ECMs for physiologically relevant ***,accurate reproduction of the 3D hierarchical and nonuniform mechanical stffness inside one integrated microstructure to mimic the complex mechanical properties of native ECMs presents a major ***,by using digital holographic microscopy(DHM)-based stffness imaging feedback,we propose a novel closed-loop control algorithm to achieve high-accuracy control of mechanical properties for hydrogel microstructures that recapitulate the physiological properties of native ECMs with high *** photoprinting,the photocuring area of the hydrogel is divided into microscale grid areas to locally control the photocuring *** the assistance of a motorized microfluidic channel,the curing thickness is controlled with layer-by-layer *** DHM-based stiffness imaging feedback allows accurate adjustment of the photocuring degree in every grid area to change the crosslinking network density of the hydrogel,thus enabling large-span and high-resolution modulation of mechanical ***,the gelatin methacrylate was used as a typical biomaterial to construct the highfidelity biomimetic *** Young's modulus could be flexibly modulated in the 10 kPa to 50 kPa ***,the modulus gradient was accurately controlled to within 2.9 *** engineering ECM with locally different mechanical properties,cell spreading along the stff areas was observed *** believe that this method can regenerate complex biomimetic ECMs that closely recapitulate in-vivo mechanical properties for further applications in tissue engineering and biomedical research.

关键词： microstructure ECM curing

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Editorial

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Mathematics and Computers in Simulation 1996年第5-6期40卷 505-506页

作者： Spyros G. Tzafestas Intelligent Robotics and Control Unit National Technical University of Athens Athens Greece

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Second Generation Diagnostic Expert Systems: Requirements, Architectures and Prospects

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IFAC Proceedings Volumes 1991年第6期24卷 327-332页

作者： S. Tzafestas Intelligent Robotics and Control Unit (IRCU) Computer Science Division National Technical University of Athens Zografou 15773 Athens Greece

An introduction to second-generation expert systems is provided starting with a discussion of the limitations of first-generation systems. A few architectures proposed for the second-generation expert systems are reviewed, a tour on the expert systems approach to fault diagnostic/control system design is made, and some issues that must be addressed in future works are highlighted. A sketch of a deep expert system developed by the author’s group is also provided.

关键词： First-generation expert systems second-generation expert systems problem-solving flexibility human-computer interaction expert system extensibility deep models reasoning from structure and behaviour nonmonotonic reasoning

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Neural networks in robotics: state of the art

Neural networks in robotics: state of the art

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： S.G. Tzafestas Intelligent Robotics and Control Unit Department of Electrical and Computer Engineering National and Technical University of Athens Athens Greece

This paper provides a short review of the neural network approach to system control with reference to robotic systems. Starting with an exposition of the main neurocontrol architectures, the paper overviews the literature on the application of neural networks to robot kinematics, dynamics, path planning and motion control, including some work on neurofuzzy control. To appreciate better robot neurocontrol, an unsupervised robot neurocontroller is presented in some detail. The paper includes a discussion of the criticism made to the neural control paradigms, and an outline of some interesting areas for further research.

关键词： Neural networks intelligent networks control systems Automatic control Biological neural networks Neurons intelligent robots Adaptive control Neurocontrollers Humans

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A study of the generalization capability versus training in backpropagation neural networks

A study of the generalization capability versus training in ...

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IEEE International Conference on Systems, Man and Cybernetics

作者： P.J. Dalianis S.G. Tzafestas G. Anthopoulos Intelligent Robotics and Control Unit (IRCU) Computer Science Division National and Technical University of Athens Athens Greece

The phenomenon of overtraining in backpropagation neural networks is discussed. The relationships between network size, training set size and generalization capabilities are examined. An extension to an existing algorithm of backpropagation is described. The extended algorithm provides a new energy function and its advantages, such as improved plasticity and performance, along with its dynamic properties, are explained. The algorithm is applied to some common problems and simulation results are presented and discussed.< >

关键词： intelligent networks Neural networks Backpropagation algorithms Multi-layer neural network intelligent robots Testing Function approximation Vectors intelligent control Robot control

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On Line Discrete-Time control of Industrial Robots

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IFAC Proceedings Volumes 1991年第9期24卷 141-147页

作者： A. Zagorianos S. Tzafestas G. Stavrakakis Intelligent Robotics and Control Unit National Technical University of Athens Zografou 157 73 Athens Greece Department of Production Engineering Technical University of Crete Chania Crete

A recent discrete-time robotic model is employed and linearized to develop three different LQ-type robot controllers, namely optimal time-varying linear-quadratic controller (OTVLQ), OTVLQ controller with steady-state error elimination, and one-step ahead optimal LQ controller. These controllers require moderate computational effort and are suitable for microprocessor-based implementation. Experimental results on a KUKA IR 160/15 robotic model verified the success and efficiency of the controllers.

关键词： Industrial robots discrete-time control robot discrete model optimal control LQ control one-step-ahead control

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Fault diagnosis in complex systems using artificial neural networks

Fault diagnosis in complex systems using artificial neural n...

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IEEE Conference on control Technology and Applications (CCTA)

作者： Tzafestas Dalianis Intelligent Robotics and Control Unit (IRCU) Computer Science Division Electrical & Computer Engineering Department National and Technical University of Athens Athens Greece

Very complex technical and other physical processes require sophisticated methods of fault diagnosis and online condition monitoring. Various conventional techniques have already been well investigated and presented in the literature. However, in the last few years, a lot of attention has been given to adaptive methods based on artificial neural networks, which can significantly improve the symptom interpretation and system performance in a case of malfunctioning. Such methods are especially considered in cases where no explicit algorithms or models for the problem under investigation exist. In such problems, automatic interpretation of faulty symptoms with the use of artificial neural network classifiers is recommended. Two different models of artificial neural networks, the extended backpropagation and the radial basis function, are discussed and applied with appropriate simulations for a real world applications in a chemical manufacturing plant.< >

关键词： Feedforward neural networks Backpropagation Fault diagnosis Large-scale systems Chemical industry Neural network applications

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Book review xx + 236 pp Integration, coordination and control of multisensor robot systems , Hugh F. Durrant-Whyte , Kluwer Academic Publishers ( 1988 )

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robotics and Autonomous Systems 1990年第3期6卷 315-315页

作者： Spyros Tzafestas Intelligent Robotics and Control Unit NTUA Athens Greece

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Fuzzy controller design using the mean-value-based functional reasoning

Fuzzy controller design using the mean-value-based functiona...

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International Joint Conference on Neural Networks (IJCNN)

作者： K. Watanabe K. Hara S.G. Tzafestas Department of Mechanical Engineering Saga University Saga Japan Graduate School of Science and Engineering Saga University Saga Japan Intelligent Robotics and Control Unit Computer Science Division National and Technical University of Athens Athens Greece

A new fuzzy reasoning is proposed so that the conclusion consists of a function of mean-values on each membership function in antecedent. It is then shown that the constant parameters in conclusion can be rationally designed from the view point of a control theory, if the conclusion is regarded as a sliding controller with the mean values in antecedent as state variables.

关键词： Fuzzy control Fuzzy reasoning Sliding mode control control theory intelligent robots Input variables Mechanical engineering intelligent control Robot control Computer science

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Micro Robotic Manipulation System for the Force Stimulation of Muscle Fiber-like Cell Structure

Micro Robotic Manipulation System for the Force Stimulation ...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Xie Chen Qing Shi Shingo Shimoda Tao Sun Huaping Wang Qiang Huang Toshio Fukuda Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing China Intelligent Robotics Institute School of Mechatronical Engineering Beijing Institute of Technology Beijing China Intelligent Behavior Control Collaboration Unit RIKEN Center of Brain Science Nagoya Japan Key Laboratory of Biomimetic Robots and Systems Beijing Institute of Technology Ministry of Education Beijing China Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing China

Many previous works have facilitated muscle cell (C2C12) alignment to form fiber-like cell structures. However, there still remains a challenge how to induce C2C12 myoblasts in the cell structures to differentiate into matured myocytes to form a functional muscle tissue, while external mechanical stimulation has been proved to have good effects on proliferation and differentiation of myoblasts. In this paper, we proposed a vision-based micro robotic manipulation system to achieve automatic mechanical stimulation for one single muscle fiber-like cell structures (MFCS). A tube, which is attached to a three degree-of-freedom (DOF) manipulator, and a probe are employed to apply the uniaxial mechanical stimulation to train the MFCS. To measure the force applied on MFCS, a vision-based measuring and correction method is utilized, which decrease the error by 74%. Moreover, based on the viscoelastic property of the MFCS, a feedback control algorithm has been applied to compensate for the force loss to realize the force stimulation. And the final value of force remains 699 ± 1μN after 110s experiment.

关键词： Force measurement Force Measurement uncertainty Muscles Manipulators Feedback control Electron tubes

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