Automated Micromanipulation of Micro Objects

In recent years, research efforts in the development of Micro Electro Mechanical Systems, (MEMS) including microactuators and micromanipulators, have attracted a great deal of attention. The development of microfabrication techniques has resulted in substantial progress in the miniaturization of devices such as electronic circuits. However, the research in MEMS still lags behind in terms of the development of reliable tools for post-fabrication processes and the precise and dexterous manipulation of individual micro size objects. Current micromanipulation mechanisms are prone to high costs, a large footprint, and poor dexterity and are labour intensive. To overcome such, the research in this thesis is focused on the utilization of microactuators in micromanipulation. Microactuators are compliant structures. They undergo substantial deflection during micromanipulation due to the considerable surface micro forces. Their dominance in governing micromanipulation is so compelling that their effects should be considered in designing microactuators and microsensors. In this thesis, the characterization of the surface micro forces and automated micromanipulation are investigated. An inexpensive experimental setup is proposed as a platform to replace Atomic Force Microscopy (AFM) for analyzing the force characterization of micro scale components. The relationship between the magnitudes of the surface micro forces and the parameters such as the velocity of the pushing process, relative humidity, temperature, hydrophilicity of the substrate, and surface area are empirically examined. In addition, a precision automated micromanipulation system is realized. A class of artificial neural networks (NN) is devised to estimate the unmodelled micro forces during the controlled pushing of micro size object along a desired path. Then, a nonlinear controller is developed for the controlled pushing of the micro objects to guarantee the stability of the closed loop system in the Lyapunov sense. To validate the performance of the proposed controller, an experimental setup is designed. The application of the proposed controller is extended to precisely push several micro objects, each with different characteristics in terms of the surface micro forces governing the manipulation process. The proposed adaptive controller is capable of learning to adjust its weights effectively when the surface micro forces change under varying conditions. By using the controller, a fully automated sequential positioning of three micro objects on a flat substrate is performed. The results are compared with those of the identical sequential pushing by using a conventional linear controller. The results suggest that artificial NNs are a promising tool for the design of adaptive controllers to accurately perform the automated manipulation of multiple objects in the microscopic scale for microassembly

Optically manipulated control over micron-scale signalling dynamics for directing cellular differentiation and migration

Cellular microenvironments are an important area of study, and their implications with regard to development, tissue function, and disease, mean that they have particular relevance in tissue engineering. The development of tissue engineered therapeutics is underpinned by the understanding of how the cells exist in their natural environment. A fundamental lack of insight into the signalling mechanisms within microenvironments, due to in part a lack of appropriate technologies, has meant that the therapeutic potential of tissue engineering is limited. To this end, the development of a micropatterning technology that enables control over solute signalling dynamics on the micron scale has been investigated. A bespoke holographic optical tweezers (HOTs) system was used to precisely position cells and controlled release vehicles into three-dimensional arrangements that resemble basic cellular micro-architectures. Via optical manipulation, release vehicles could be patterned to create solute release patterns to mimic signalling events in vitro. A proof of concept was established to demonstrate fluorophore release from microparticles positioned with high precision, into previously unobtainable micron-scale patterns. Such developments required optimisation of the system and protocols, for use with cell and microparticle manipulation and, creating a tool-set suitable for address unsolved biological questions. Biological investigations were completed to demonstrate how the HOTs can be used to control zonal cell differentiation and migration. These processes are paramount to cell microenvironment function, and this study has shown that the HOTs patterning setup is capable of achieving such signalling models in vitro. Herein is presented compelling evidence that optically manipulated release sources can achieve new levels of precision over signalling dynamics, over the length scales suitable for even the smallest cell microenvironments. It is hoped that through the better in vitro modelling of such cellular microenvironments and other signalling events, investigators will be able to elucidate new mechanisms through which cells proliferate and function

Real-Time Path Planning for Automating Optical Tweezers based Particle Transport Operations

Optical tweezers (OT) have been developed to successfully trap, orient, and transport micro and nano scale components of many different sizes and shapes in a fluid medium. They can be viewed as robots made out of light. Components can be simply released from optical traps by switching off laser beams. By utilizing the principle of time sharing or holograms, multiple optical traps can perform several operations in parallel. These characteristics make optical tweezers a very promising technology for creating directed micro and nano scale assemblies. In the infra-red regime, they are useful in a large number of biological applications as well. This dissertation explores the problem of real-time path planning for autonomous OT based transport operations. Such operations pose interesting challenges as the environment is uncertain and dynamic due to the random Brownian motion of the particles and noise in the imaging based measurements. Silica microspheres having diameters between (1-20) µm are selected as model components. Offline simulations are performed to gather trapping probability data that serves as a measure of trap strength and reliability as a function of relative position of the particle under consideration with respect to the trap focus, and trap velocity. Simplified models are generated using Gaussian Radial Basis Functions to represent the data in a compact form. These metamodels can be queried at run-time to obtain estimated probability values accurately and efficiently. Simple trapping probability models are then utilized in a stochastic dynamic programming framework to compute optimum trap locations and velocities that minimizes the total, expected transport time by incorporating collision avoidance and recovery steps. A discrete version of an approximate partially observable Markov decision process algorithm, called the QMDP_NLTDV algorithm, is developed. Real-time performance is ensured by pruning the search space and enhancing convergence rates by introducing a non-linear value function. The algorithm is validated both using a simulator as well as a physical holographic tweezer set-up. Successful runs show that the automated planner is flexible, works well in reasonably crowded scenes, and is capable of transporting a specific particle to a given goal location by avoiding collisions either by circumventing or by trapping other freely diffusing particles. This technique for transporting individual particles is utilized within a decoupled and prioritized approach to move multiple particles simultaneously. An iterative version of a bipartite graph matching algorithm is also used to assign goal locations to target objects optimally. As in the case of single particle transport, simulation and some physical experiments are performed to validate the multi-particle planning approach

Optically manipulated control over micron-scale signalling dynamics for directing cellular differentiation and migration

Cellular microenvironments are an important area of study, and their implications with regard to development, tissue function, and disease, mean that they have particular relevance in tissue engineering. The development of tissue engineered therapeutics is underpinned by the understanding of how the cells exist in their natural environment. A fundamental lack of insight into the signalling mechanisms within microenvironments, due to in part a lack of appropriate technologies, has meant that the therapeutic potential of tissue engineering is limited. To this end, the development of a micropatterning technology that enables control over solute signalling dynamics on the micron scale has been investigated. A bespoke holographic optical tweezers (HOTs) system was used to precisely position cells and controlled release vehicles into three-dimensional arrangements that resemble basic cellular micro-architectures. Via optical manipulation, release vehicles could be patterned to create solute release patterns to mimic signalling events in vitro. A proof of concept was established to demonstrate fluorophore release from microparticles positioned with high precision, into previously unobtainable micron-scale patterns. Such developments required optimisation of the system and protocols, for use with cell and microparticle manipulation and, creating a tool-set suitable for address unsolved biological questions. Biological investigations were completed to demonstrate how the HOTs can be used to control zonal cell differentiation and migration. These processes are paramount to cell microenvironment function, and this study has shown that the HOTs patterning setup is capable of achieving such signalling models in vitro. Herein is presented compelling evidence that optically manipulated release sources can achieve new levels of precision over signalling dynamics, over the length scales suitable for even the smallest cell microenvironments. It is hoped that through the better in vitro modelling of such cellular microenvironments and other signalling events, investigators will be able to elucidate new mechanisms through which cells proliferate and function