Characterization and Validation of a Novel Robotic System for Fluid-Mediated Programmable Stochastic Self-Assembly

Several self-assembly systems have been developed in recent years, where depending on the capabilities of the building blocks and the controlability of the environment, the assembly process is guided typically through either a fully centralized or a fully distributed control approach. In this work, we present a novel experimental system for studying the range of fully centralized to fully distributed control strategies. The system is built around the floating 3-cm-sized Lily robots, and comprises a water-filled tank with peripheral pumps, an overhead camera, an overhead projector, and a workstation capable of controlling the fluidic flow field, setting the ambient luminosity, communicating with the robots over radio, and visually tracking their trajectories. We carry out several experiments to characterize the system and validate its capabilities. First, a statistical analysis is conducted to show that the system is governed by reaction diffusion dynamics, and validate the applicability of the standard chemical kinetics modeling. Additionally, the natural tendency of the system for structure formation subject to different flow fields is investigated and corresponding implications on guiding the self-assembly process are discussed. Finally, two control approaches are studied: 1) a fully distributed control approach and 2) a distributed approach with additional central supervision exhibiting an improved performance. The formation time statistics are compared and a discussion on the generalization of the method is provided

3D Assembly For Programmable Matter And Hollow Fiber Membrane Gas Exchange In Planar Photobioreactors

In my Ph.D. research I have applied mechanical engineering knowledge and approaches to develop technologies for two topics: programmable matter and green energy through biofuels. Specifically, I have addressed the issues of 3D assembly in a fluid environment and gas exchange in photobioreactors. In the first part of this dissertation, I investigated a programmable matter system that consists of cm-scale building blocks which are agitated in a stochastic flow pattern and assembled using local fluid forces. The fundamental aspect of this approach that my research concentrated on was the problem of component alignment. Towards this end we developed a novel alignment strategy and characterized it using a combination of numerical simulations and experiments. In the second part of this dissertation, I demonstrate the optimal geometric and operational conditions for CO2 transport to planar cultures of photosynthetic organisms via hollow fiber membranes. Firstly, I examined the growth pattern of Synechococcus elongatus around individual hollow fiber membranes to determine the optimal spacing and conditions for maximizing photosynthetic activity. I expanded on this initial work and used the information from the single fiber experiments to design, fabricate, and characterize arrays of HFM fibers. By using this novel configuration of hollow fiber membranes, I was able to grow and sustain an organism culture with effectiveness comparable to state of the art methods while eliminating the need for media circulation and replenishment and allowing for integration into waveguide photobioreactors

The Propulsion of Reconfigurable Modular Robots in Fluidic Environments

Reconfigurable modular robots promise to transform the way robotic systems are designed and operated. Fluidic or microgravity environments, which can be difficult or dangerous for humans to work in, are ideal domains for the use of modular systems. This thesis proposes that combining effective propulsion, large reconfiguration space and high scalability will increase the utility of modular robots. A novel concept for the propulsion of reconfigurable modular robots is developed. Termed Modular Fluidic Propulsion (MFP), this concept describes a system that propels by routing fluid though itself. This allows MFP robots to self-propel quickly and effectively in any configuration, while featuring a cubic lattice structure. A decentralized occlusion-based motion controller for the system is developed. The simplicity of the controller, which requires neither run-time memory nor computation via logic units, combined with the simple binary sensors and actuators of the robot, gives the system a high level of scalabilty. It is proven formally that 2-D MFP robots are able to complete a directed locomotion task under certain assumptions. Simulations in 3-D show that robots composed of 125 modules in a variety of configurations can complete the task. A hardware prototype that floats on the surface of water is developed. Experiments show that robots composed of four modules can complete the task in any configuration. This thesis also investigates the evo-bots, a self-reconfigurable modular system that floats in 2-D on an air table. The evo-bot system uses a stop-start propulsion mechanism to choose between moving randomly or not moving at all. This is demonstrated experimentally for the first time. In addition, the ability of the modules to detect, harvest and share energy, as well as self-assemble into simple structures, is demonstrated

Modular Hydraulic Propulsion: A Robot that Moves by Routing Fluid Through Itself

This paper introduces the concept of Modular Hydraulic Propulsion, in which a modular robot that operates in a fluid environment moves by routing the fluid through itself. The robot’s modules represent sections of a hydraulics network. Each module can move fluid between any of its faces. The modules (network sections) can be rearranged into arbitrary topologies. We propose a decentralized motion controller, which does not require modules to communicate, compute, nor store information during run-time. We use 3-D simulations to compare the performance of this controller to that of a centralized controller with full knowledge of the task. We also detail the design and fabrication of six 2-D prototype modules, which float in a water tank. Results of systematic experiments show that the decentralized controller, despite its simplicity, reliably steers modular robots towards a light source. Modular Hydraulic Propulsion could offer new solutions to problems requiring reconfigurable systems to move precisely in 3-D, such as inspection of pipes, vascular systems or other confined spaces

Automated Real-Time Control of Fluidic Self-Assembly of Microparticles

Self-assembly is a key coordination mechanism for large multi-unit systems and a powerful bottom-up technology for micro/nanofabrication. Controlled self-assembly and dynamic reconfiguration of large ensembles of microscopic particles can effectively bridge these domains to build innovative systems. In this perspective, we present SelfSys, a novel platform for the automated control of the fluidic self-assembly of microparticles. SelfSys centers around a water-filled microfluidic chamber whose agitation modes, induced by a coupled ultrasonic actuator, drive the assembly. Microparticle dynamics is imaged, tracked and analyzed in real-time by an integrated software framework, which in turn algorithmically controls the agitation modes of the microchamber. The closed control loop is fully automated and can direct the stochastic assembly of microparticle clusters of preset dimension. Control issues specific to SelfSys implementation are discussed, and its potential applications presented. The SelfSys platform embodies at microscale the automated self-assembly control paradigm we first demonstrated in an earlier platform

Autonomous Task-Based Evolutionary Design of Modular Robots

In an attempt to solve the problem of finding a set of multiple unique modular robotic designs that can be constructed using a given repertoire of modules to perform a specific task, a novel synthesis framework is introduced based on design optimization concepts and evolutionary algorithms to search for the optimal design. Designing modular robotic systems faces two main challenges: the lack of basic rules of thumb and design bias introduced by human designers. The space of possible designs cannot be easily grasped by human designers especially for new tasks or tasks that are not fully understood by designers. Therefore, evolutionary computation is employed to design modular robots autonomously. Evolutionary algorithms can efficiently handle problems with discrete search spaces and solutions of variable sizes as these algorithms offer feasible robustness to local minima in the search space; and they can be parallelized easily to reducing system runtime. Moreover, they do not have to make assumptions about the solution form. This dissertation proposes a novel autonomous system for task-based modular robotic design based on evolutionary algorithms to search for the optimal design. The introduced system offers a flexible synthesis algorithm that can accommodate to different task-based design needs and can be applied to different modular shapes to produce homogenous modular robots. The proposed system uses a new representation for modular robotic assembly configuration based on graph theory and Assembly Incidence Matrix (AIM), in order to enable efficient and extendible task-based design of modular robots that can take input modules of different geometries and Degrees Of Freedom (DOFs). Robotic simulation is a powerful tool for saving time and money when designing robots as it provides an accurate method of assessing robotic adequacy to accomplish a specific task. Furthermore, it is difficult to predict robotic performance without simulation. Thus, simulation is used in this research to evaluate the robotic designs by measuring the fitness of the evolved robots, while incorporating the environmental features and robotic hardware constraints. Results are illustrated for a number of benchmark problems. The results presented a significant advance in robotic design automation state of the art

Design, development and application of an automated framework for cell growth and laboratory evolution

Precise control over microbial cell growth conditions could enable detection of minute phenotypic changes, which would improve our understanding of how genotypes are shaped by adaptive selection. Although automated cell- culture systems such as bioreactors offer strict control over liquid culture conditions, they often do not scale to high-throughput or require cumbersome redesign to alter growth conditions. I report the design and validation of eVOLVER, a scalable DIY framework that can be configured to carry out high- throughput growth experiments in molecular evolution, systems biology, and microbiology. I perform high-throughput evolution of yeast across systematically varied population density niches to show how eVOLVER can precisely characterize adaptive niches. I describe growth selection using time-varying temperature programs on a genome-wide yeast knockout library to identify strains with altered sensitivity to changes in temperature magnitude or frequency. Inspired by large-scale integration of electronics and microfluidics, I also demonstrate millifluidic multiplexing modules that enable multiplexed media routing, cleaning, vial-to-vial transfers and automated yeast mating

Stochastic folding for chain programmable matter

Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 57-59).The vision of programmable matter is to create a blob of material that can transform itself into an arbitrary form. One promising approach for achieving programmable matter is to construct a chain of identical nodes that can fold into arbitrary threedimensional shapes. Previous active electromechanical systems have demonstrated this concept but are currently costly, complex, and not robust enough to scale to smaller sizes or larger numbers of nodes. The goal of this thesis is to explore methods of simplifying chain programmable matter by removing the actuator from each node and, instead, putting energy into the system externally through stochastic vibrations. Each node takes this random energy input and rectifies it to produce motion towards the target position. We propose two variants of this system: 1) smart clutches that can be reprogrammed in situ and fold through arbitrary paths in configuration space and 2) ratchets that are programmed ahead of time and are entirely passive. We developed a chain using the ratchet concept and also constructed a new active, electromechanical chain with reduced cost and improved speed and torque compared to previous electromechanical systems. Through experimental and computer simulated studies, we determined that stochastic actuation can simplify and reduce the cost of these systems. We have also identified how the size of the increments of the ratchet, length of the chain, and the amplitude and frequency of agitation affect the folding time and success rate. In addition, we show that passive folding systems should improve in performance as the hardware scales down.by Maxim B. Lobovsky.S.M

Enabling Capillary Self-Assembly for Microsystem Integration

Efficient and precise assembly of very-large quantities of sub-millimeter-sized devices onto pre-processed substrates is presently a key frontier for microelectronics, in its aspiration to large-scale mass production of devices with new functionalities and applications (e.g. thin dies embedded into flexible substrates, 3D microsystem integration). In this perspective, on the one hand established pick&place assembly techniques may be unsuitable, due to a trade-off between throughput and placement accuracy and to difficulties in predictably handling very-small devices. On the other hand, self-assembly processes are massively parallel, may run unsupervised and allow contactless manipulation of objects. The convergence between robotic assembly and self-assembly, epitomized by capillarity-enhanced flip-chip assembly, can therefore enable an ideal technology meeting short-to-medium-term electronic packaging and assembly needs. The objective of this thesis is bridging the gap between academic proofs-of- concept of capillary self-assembly and its industrial application. Our work solves several issues relevant to capillary self-assembly of thin dies onto preprocessed substrates. Very-different phenomena and aspects of both scientific and technological interest coexist in such a broad context. They were tackled both experimentally and theoretically. After a critical review of the state-of-the-art in microsystem integration, a complete quasi-static study of lateral capillary meniscus forces is presented. Our experimental setup enables also a novel method to measure the contact angle of liquids. Recessed binding sites are introduced to obtain perfectly-conformal fluid dip-coating of patterned surfaces, which enables the effective and robust coding of geometrical information into binding sites to direct the assembly of parts. A general procedure to establish solder-mediated electro-mechanical interconnections between parts and substrate is validated. Smart surface chemistries are invoked to solve the issue of mutual adhesion between parts during the capillary self-assembly process. Two chemical kinetic-inspired analytic models of fluidic self-assembly are presented and criticized to introduce a novel agent-based model of the process. The latter approach allows realistic simulations by taking into account spatial factors and collision dynamics. Concluding speculations propose envisioned solutions to residual open issues and further perspectives for this field of rapidly-growing importance