Michael T. Tolley

Dynamically programmable fluidic assembly

A major challenge in fluidic assembly is the dynamically programmable fabrication of arbitrary geometries from basic components. Current approaches require predetermination of either the assembly machinery or the component interfaces for the specific target geometries. We present an alternative concept that exploits self-assembly forces locally but directs these forces globally, allowing fabrication and manipulation of target structures without tailoring the substrate or interfaces. By controlling the flow in a microfluidic chamber, components are directed to their target locations where local interactions align and bond them. Following this approach, we demonstrate and quantify the experimental assembly of structures composed of two to ten components.

Stochastic Modular Robotic Systems: A Study of Fluidic Assembly Strategies

Modular robotic systems typically assemble using deterministic processes where modules are directly placed into their target position. By contrast, stochastic modular robots take advantage of ambient environmental energy for the transportation and delivery of robot components to target locations, thus offering potential scalability. The inability to precisely predict component availability and assembly rates is a key challenge for planning in such environments. Here, we describe a computationally efficient simulator to model a modular robotic system that assembles in a stochastic fluid environment. This simulator allows us to address the challenge of planning for stochastic assembly by testing a series of potential strategies. We first calibrate the simulator using both high-fidelity computational fluid-dynamics simulations and physical experiments. We then use this simulator to study the effects of various system parameters and assembly strategies on the speed and accuracy of assembly of topologically different target structures.

On-line assembly planning for stochastically reconfigurable systems

Stochastic assembly approaches can reduce the power, computation, and/or actuation demands on assembly systems by taking advantage of probabilistic processes. At the same time, however, they relinquish the efficiency and predictability of deterministic alternatives. This makes planning error-free assembly sequences challenging, particularly in the face of changing environmental conditions or goals. Here we address these challenges with an on-line approach to assembly planning for stochastically reconfigurable systems where the spatial and temporal availability of modules is uncertain, either due to a stochastic assembly mechanism, resource fluctuations, or large numbers of uncoordinated agents. We propose an assembly algorithm that is guaranteed to find an assembly path for finite-sized, connected objects. This is achieved by sampling the space of possible assembly paths to the target structure that satisfy assembly constraints. Assembly is accelerated by pursuing multiple paths in parallel. The algorithm computes these parallel assembly paths on-line during assembly and is thus able to adapt to changing conditions, as well as predict the remaining assembly time. For situations where the number of paths found exceeds the number that can be pursued in parallel, the assembly algorithm further maximizes assembly rates according to domain-specific local assembly costs.

Fluidic manipulation for scalable stochastic 3D assembly of modular robots

One of the grand challenges of self-reconfiguring modular robotics is the assembly of a functional system from thousands of components. However, to date, only systems comprised of small numbers of modules have been demonstrated. One approach to scaling to large numbers of modules is to simplify module design by relieving the modules of the typical power, control, and actuation requirements necessary for locomotion. Assembly is accomplished by taking advantage of stochastic environmental motions to move the modules into place. Here we present an experimental system in which we assemble 3D target structures stochastically from simple, 15 mm-scaled components by manipulating the fluid flow in a 1.3 L tank. We also demonstrate fundamental assembly and repair operations experimentally, and discuss initial assembly statistics.

Hydrodynamically Tunable Affinities for Fluidic Assembly

Most current micro- and nanoscale self-assembly methods rely on static, preprogrammed assembly affinities between the assembling components such as capillarity, DNA base pair matching, and geometric interactions. While these techniques have proven successful at creating relatively simple and regular structures, it is difficult to adapt these methods to enable dynamic reconfiguration of the structure or on-the-fly error correction. Here we demonstrate a technique to hydrodynamically tune affinities between assembling components by direct thermal modulation of the local viscosity field surrounding them. This approach is shown here for two-dimensional silicon elements of 500 microm length using a thermorheological fluid that undergoes reversible sol-gel transition on heating. Using this system, we demonstrate the ability to dynamically change the assembly point in a fluidic self-assembly process and selectively attract and reject elements from a larger structure. Although this technique is demonstrated here for a small number of passive mobile components around a fixed structure, it has the potential to overcome some of the limitations of current static affinity based self-assembly.

Evolutionary Design and Assembly Planning for Stochastic Modular Robots

A persistent challenge in evolutionary robotics is the transfer of evolved morphologies from simulation to reality, especially when these morphologies comprise complex geometry with embedded active elements. In this chapter we describe an approach that automatically evolves target structures based on functional requirements and plans the error-free assembly of these structures from a large number of active components. Evolution is conducted by minimizing the strain energy in a structure due to prescribed loading conditions. Thereafter, assembly is planned by sampling the space of all possible paths to the target structure and following those that leave the most options open. Each sample begins with the final completed structure and removes one accessible component at a time until the existing substructure is recovered. Thus, at least one path to a complete target structure is guaranteed at every stage of assembly. Automating the entire process represents a step towards an interactive evolutionary design and fabrication paradigm, similar to that seen in nature.

Interfacing methods for fluidically-assembled microcomponents

Here we present the design and implementation of electrical and mechanical interfaces for fluidically-assembled planar MEMS. We discuss the design and fabrication of systems of passive mechanical latches to bond microcomponents together and of electrical layers capable of establishing electrical connections with each other. We evaluate the ability of components with these interfaces to bond together within a microfluidic channel and to establish electrical circuits when assembled. This work supports the development of a novel microassembly strategy that bridges the gap between bottom-up self-assembly and top-down direct-manipulation technique. The ultimate goal of this research is the development of MEMS devices capable of the on-demand self-assembly, repair, and reconfiguration.

Increased robustness for fluidic self-assembly

Self-assembly methods have been developed at the micro- and nanoscale to create functional structures from subelements stochastically dispersed in a fluid. Self-assembly paradigms have limitations in terms of achievable complexity of the final structure, ability to perform error correction, and scalability. Fluidic self-assembly attempts to overcome these limitations by incorporating a controlled flow structure and/or complex geometric interactions to improve the assembly rate and the specificity of the final positioning. Since the initial position and orientation of a subelement in a stochastic system are indeterminate, the most robust of these schemes are those for which the dependence on the initial condition will be the weakest. In this paper we develop an analytical/numerical model for the fluid forces and torques on a two-dimensional subelement involved in a fluidic self-assembly process and describe the translational and rotational motions of the element due to these forces. We use this model to de...

DIRECTED HIERARCHICAL SELF ASSEMBLY - ACTIVE FLUID MECHANICS AT THE MICRO AND NANOSCALES

Directed hierarchical self assembly (DHSA) involves the purposeful assembly of a series of different subunits over multiple length scales to create arbitrarily shaped, large structures. We are developing a two stage DHSA procedure comprising of a coarse “far field” fluidic process which brings the sub-elements into the general vicinity of the assembly point and a fine “near field” process which completes the process. In the experiments presented here our sub-elements comprise of lithographically patterned silicon “microtiles” which are 500μm in size and contain a series of functional elements. The far-field assembly of these tiles is controlled fluid dynamically by modulating the translational and rotational shear forces applied to the tiles with a microfluidic structure. The near-field assembly is controlled through on board (i.e. on tile) microchannel jets/sinks, the strengths of which are modulated through the assembly or disassembly of thermally actuated gel based microvalves. This provides two fundamental levels of system control, namely control of the magnitude and direction of fluid flow, as well as addressability and control of each assembled component through on tile valves. In this paper we present our preliminary work on the fundamental fluid mechanics of this assembly at these two stages. In the first section we look at fluid motion and forces using CFD based numerical simulations. In the second we study a valving system based on an aqueous solution of a triblock copolymers that form a gel at temperatures near room temperature.Copyright