Session Q14: Functionality through Nonlinearity in Soft Robotics

Enhanced functionality through dynamic effects of magneto rheological elastomers

Magneto-rheological elastomers (MREs) are composite elastic materials that undergo large deformations when subjected to magnetic fields. Structural mechanisms made of MREs have been exploited as actuators in fields ranging from microfluidics to soft robotics. To facilitate the design cycle in these classes of systems, several structural theories for magneto-active beams, rods, plates, and shells have recently been proposed. However, these existing modeling frameworks mostly focus on time-independent magnetic fields. Dynamic effects resulting from time-varying magnetic fields are rarely considered. Here, we investigate an experimental system to explore the dynamic response of an MRE beam under oscillatory magnetic driving. We characterize the dynamics of the structure, including its damping characteristics, as a function of the driving parameters. The gathered understanding is then leveraged to design an MRE bistable actuator that can snap through with a tunable critical load. We believe our results will inform the development of more efficient actuation mechanisms for MRE structures.

    

Bioinspired Soft Metamaterials for Soft Robotic Applications

In the field of soft robotics, the nonlinearities and large deformations typical of elastomeric materials are used to emulate complex phenomena typical of the animal kingdom. Introducing metamaterials further expands the design space of soft robotics, unlocking interesting and useful mechanical properties and granting novel functionalities to components. Here, we study a soft metamaterial that undergoes a global pattern reconfiguration due to buckling instability upon inflation. Studies thus far have induced global buckling instability through uniaxial compression or negative pressure, but we will introduce and leverage, for the first time, a global buckling instability due to positive pressure in a porous metamaterial. Both numerical and experimental approaches will be used to obtain pressure-volume curves and to characterize the buckling modes based on the geometrical properties of the 3D porous metamaterial. We will show how the buckling-induced reconfigurable and reversible behavior can be harnessed for gripping and sequential actuation purposes. Leveraging this instability as a means for actuation, we explore a new class of programmable soft actuators with distributed gripping and embedded sequencing capabilities.

    

Snap ori-kirigami of inflatable actuators

Soft actuators with significant morphing capabilities perform diverse tasks through reconfiguration of their mechanical properties. However, shape shifting of soft machines often requires complex mechanisms with individual control method for each function. Here, we present a simple, versatile mechanism for soft inflatable actuators with reversible modularity stimulated by pneumatic snap-through of bistable shells. We interconnect pneumatic networks (pneu-nets) integrated with spherical shells and use this mechanism to construct ori-kirigami designs that can fold and deploy into diverse structures. By controlling the snap-through criteria of shells, this snap ori-kirigami pneu-net can shape-shift into various modes performing multiple discrete functions through single pressure input control. The reconfigured structure can also be maintained without the constant supply of pressure, enabling separate actuation of each mode. We demonstrate this system through ori-kirigami designs, '3D spinning ball' and '2D quad-tessellation', to create soft robots capable of morphing and performing multiple functions. Our study provides a novel mechanism for the design and control of inflatable soft devices that can reversibly transform in shape and function.   

Shape morphing soft membranes via machine learning

Across fields of science, researchers have increasingly focused on designing soft devices that can shape-morph to achieve functionality. However, identifying a rest shape that leads to a target 3D shape upon actuation is a non-trivial task that involves inverse design capabilities. In this study, a simple and efficient platform is presented to design pre-programmed 3D shapes starting from 2D planar composite membranes. By training neural networks with a small set of finite element simulations, the authors are able to obtain both the optimal design for a pixelated 2D elastomeric membrane and the inflation pressure required for it to morph into a target shape. The proposed method has potential to be employed at multiple scales and for different applications. As an example, it is shown how these inversely designed membranes can be used for mechanotherapy applications, by stimulating certain areas while avoiding prescribed locations.   

Elastic instability enabled shape-morphing metamaterials

The ability to change shape is important for materials in an emerging class of engineering applications including soft robots, which must be able to change shape to adapt to different environments and complete different tasks. Artificial architected structures with the ability to change shape are referred to as shape-morphing metamaterials. Several shape-morphing mechanisms have been proposed in recent years. Among them, elastic instability is one of the promising strategies with efficiency and realizability. Many morphing metamaterials lack the ability to be reprogrammed; we introduce a class of soft morphable metamaterials in which the state of the system can be programmed by exploiting the bistability of an elastic element. The result is a system in which multiple stable shapes can be achieved by reversibly changing the state of individual bistable elements via snap-through, actuated pneumatically. We characterize the operation of such a device, showing how the state of each element can be controlled and that elements may interact if placed close enough together.   

Morphing architecture with controll of both metric and curvature

  The configuration of a surface is fully characterized by two tensors, a metric tensor and a curvature tensor. Changing its shape generally involves both. With a set of constrains, the Gauss-Codazzi-Mainardi equations, the minimum of total elastic energy will dictate the final shape by setting the right metric and curvature tensor simultaneously.

  Here, we develop a versatile technique based on consumer-grade materials assembled in a flat panel, which can be designed to to program both metric and curvature. By performing theoretical analysis and experimental tests, these quantitative results are used to achieve shape-morphing and design programmed surface composed of actuators for specific tasks. Therefore, our study paves the way for a new generation of robotic systems that can tune their shape and function to adapt and even influence their surroundings, leading material machine closer to application.

    

Embodying complex deformation in soft robots via the buckling of elastomeric shells

Cylindrical shell structures made of soft materials exhibit highly complex deformation when pressurized, making them an ideal platform to realize active and adaptable robotic systems. If instead one applies vacuum, buckling is triggered---an instability that can be fully recoverable if the shells are made of an elastomeric material. Here, we show that by carefully controlling the geometry of thin-walled cylindrical shells, distinct deformations emerge during post-buckling such as contraction, twisting, and bending. We harness these vacuum-driven deformations to build soft actuators capable of programmable and complex multiaxial motion. The proposed design strategy paths a new way to fabricate soft actuators across multiple length scales, such as surgical medical devices and sampling arms for deep ocean exploration vehicles

    

Ultra-fast, programmable, and electronics-free soft robots enabled by snapping metacaps

Soft robots have a myriad of potentials because of their intrinsically compliant bodies, enabling safe interactions with humans and adaptability to unpredictable environments. However, most of them have limited actuation speeds, require complex control systems, and lack sensing capabilities. To address these challenges, here we geometrically design a class of metacaps whose rich nonlinear mechanical behaviors can be harnessed to create soft robots with unprecedented functionalities. Specifically, we demonstrate a sensor-less metacap gripper that can grasp objects in 3.75 ms upon physical contact and a pneumatically actuated gripper with tunable actuation behaviors that have little dependence on the rate of input. Both grippers can be readily integrated into a robotic platform for practical applications. Furthermore, we demonstrate that the metacap enables propelling of a swimming robot, exhibiting amplified swimming speed as well as untethered, electronics-free swimming with tunable speeds. Our metacaps provide new strategies to design the next-generation soft robots that require high transient output energy and are capable of autonomous and electronics-free maneuvering.   

High-level synthesis of soft robotic structures

To build soft robots that can process information and make autonomous decisions, we must encode intelligent responses directly in the structural dynamics, taking advantage of multistability and snapping to store state information and implement logic functions. However, elastic structures are described by partial differential equations that are both nonlinear and dissipative. Therefore, the inverse problem of designing a system for a particular response is extremely hard. In this work, we design elastic structures that execute arbitrary algorithms. We do so by taking the notion of hardware-description-language (HDL) from electronics: We describe the algorithm that the robot will execute using a mechanical description language (MDL), that we then convert to a geometry in a multi-step mechanism (Code > Logic gates > Nonlinear mass-spring model > Geometry). We demonstrate this by designing an elastic system that implements a graph search algorithm to drive a soft robot out of a maze.

    

Fluidic memory and sensing for autonomous soft robots

Soft robots are incredibly promising for many applications, e.g. object handling, bio-medical devices, and exploration of unknown environments. However, an important drawback of fluid-driven soft robots is the need for electronics and hard, bulky components, such as valves and pumps, for their control. This limits their potential in real-life applications where tethers restrain their autonomy and soft-hard interfaces limit their resilience. To overcome these limitations, we remove electronics and hard components by embedding control elements directly in the fluidic circuits.

We use a soft hysteretic valve to cyclically actuate a soft robotic limb. We develop a bi-stable pneumatic capacitor to enable two discrete behaviors for the oscillator: a high-frequency state and a low-frequency state. We then implement a memory circuit that enables switching between the two states upon opening and closing of air channels, both in a long-term and a short-term fashion. To provide useful fluidic inputs to the circuit, we develop a touch sensor based on kinking tubes. Finally, we demonstrate the potential of our approach by embedding the memory and sensing elements on a crawling soft robot. The robot changes direction upon interaction with the environment, exploring unknown spaces autonomously.

Our work shines light on the opportunities given by the integration of non-linear mechanics into fluidic circuits, towards simple yet useful behaviors in soft robots, such as autonomy.   

Integrated mechanologics for autonomous soft machines

Many biological organisms possess the capability to interact with and respond intelligently to environmental stimuli without a central computing system. This is in stark contrast to our modern electrical systems where the "intelligence" is concentrated in a central system and all input and output signals need to be converted to or from electrical signals. Building upon previous works of mechanical signal transmission systems (through transition waves) and mechanical binary computation, we present a strategy for building an unconventional class of mechanical computational intelligence, which provides a seamless interface with mechanical environments for autonomous soft machines. We show that the architected design of soft bistable elements can form into a monolithic computational platform where nondispersive elastic solitary waves propagate through networked mechanical computing units. A systematic understanding of the behavior of the solitary waves allows us to establish a general design rule for integrated mechanical computing, and its effectiveness is verified both numerically and experimentally. As a demonstration of the capability of this design strategy, we show a mimosa-inspired soft machine, which reacts differentially to mechanical inputs of varying strengths to consecutively actuate its synthetic "leaves" in different patterns. These findings would pave the way for future intelligent robots and machines that perform operations between non-electrical environmental agents.   

From mindless active particles to buckling-mediated intelligent robots

A key advantage of soft robots is their non-rigid, compliant exterior, enabling them to adapt to unknown, complex environments. Vital to this adaptability is the autonomous physical intelligence embodied in the materials used to construct soft robotic devices. Prior work has investigated the motion of soft robots constructed from designed smart materials that react to environmental heat or moisture. This work presents a simple but adaptable mode of physical intelligence. To each end of a thin, elastic beam, we attach a centimeter-scale active matter particle acting as a model engine. These particles buckle the beam that joins them and are found to run across the substrate onto which they sit. More surprisingly, these runners are observed to be able to navigate simple mazes. Here we rationalize the system's mechanics and leverage this new knowledge to systematically characterize its interactions inside the maze, e.g., making turns and passing through constrictions. As many soft robots incorporate elastic components, this work may inform the use of elasticity and active elements in navigating unstructured environments in such devices.   

The fluidic memristor: collective phenomena in flow networks of negative differential resistance

Flow networks are essential for both living organisms and engineered systems. Very often they are successfully modeled as networks of linear resistors, however, in the animal and plant circulatory system, the resistance of each element can be highly nonlinear. In some cases, it can even present regions of negative differential resistance, where the flow decreases as the pressure difference increases. Inspired by these systems, we have proposed a mathematical model for nonlinear flow networks of any topology, it includes nonlinear resitors and allows for internal accumulation/depletion of volume [1]. This model displays a wide variety of complex phenomena such as self-sustained oscillations, excitability and memory effects. We will describe this phenomenology and show how we are building such systems in the lab, where we exploit fluid-structure interactions to build tunable valves that can be arranged to create nonlinear flow networks. Finally, we will discuss an experimental system that behaves as a fluidic memristor. 

[1] M Ruiz-García, E Katifori, Emergent dynamics in excitable flow systems, Physical Review E 103 (6), 062301 (2021)   

Metafluids – Harnessing thick shell instability to program fluids

Inspired by mechanical metamaterials, we introduce the concept of a metafluid - a fluid where the mechanical response is programmed via embedded highly deformable elastic elements. In particular, we introduce into the fluid thick elastomeric spherical shells that buckle under external pressure. We first show that the highly nonlinear local behavior of these unit cells makes the global response of the fluid radically different from that of ordinary liquids in terms of compressibility, viscosity and phase transformation. Then, we show that these fluid characteristics can be controlled by tuning by the geometry of the embedded shells.  Metafluids thus provide a unique platform to enhance the capabilities of all hydraulic networks, by enabling energy absorption, disturbance rejection and even logic functionalities inside of the fluid itself.

    

A metafluid with multistable thermodynamic properties

The thermodynamic properties of fluids play a crucial role in many areas, particularly in the energy and refrigeration industries. These widespread and essential cycles are leading causes of global warming, and in particular, refrigeration was recently listed as the single most polluting technology, due to fluids used within such cycles. Creating a fluid with exceptional thermodynamic properties can thus be of great practical importance, yielding possibilities for advancement in many fields.

In this work, we study the properties of a suspension composed of a multitude of lubricated multistable capsules (structures capable of transforming between different equilibrium deformation patterns) enclosing a compressible gas and immersed within another fluid. The thermodynamic properties of the suspension are determined by an interaction between the external liquid, the encapsulated gas, and the characteristic elastic energy profile of the capsules. By leveraging the elastic multistability of the suspended capsules, we can produce a fluid with multiple stable density points for a given pressure and temperature states as well as unstable regions.

We study the pressure-density relations, and stability, of a ``metafluid”, composed of a multitude of multistable gas-filled capsules suspended in a liquid. As a simple example of a multistable capsule, we examine multiple connected bi-stable elements, produced by combining two non-identical conical frusta in opposing orientations. Bi-stability is therefore achieved by switching between extended and collapsed states through the inversion of one frustum which creates a significant change in volume. We theoretically and experimentally examine the suspension’s internal energy, equilibrium pressure-density relations, and their stability for both adiabatic and isothermal processes. We show that the elastic multistability of the capsules endows the fluid with multistable thermodynamic properties, including the ability to capture and store energy at standard atmospheric conditions, not found in naturally available fluids.