Session D21: Soft Robotic Matter I: Architected Metamaterials for Soft Robotics

Digital Logic Processes in Soft, Conductive Mechanical Materials

Information processing in soft autonomous matter has motivated the advancement of artificial materials that are capable of logic operations. With recent developments of conformable conductive composites in flexible substrates and mechanologic techniques for digital bit representation in mechanical media, an opportunity is explored here to create digital logic using conductive, compliant materials. In this research we introduce a class of soft mechanical metamaterials with programmable elastic instabilities and conductive networks that function as electronic logic gates with mechanical stress inputs. By uncovering the discrete deformation states of a metamaterial unit cell, we establish a correlation between collapse configuration and electronic conductivity of two elementary switch designs. We build upon this manifestation of unit cell switching assemblies and systematic electronic connections to realize the 6 logic gates: AND, NAND, OR, NOR, XOR, and XNOR. Additional investigation into Boolean mathematical representations of combinational logic illustrate the ability to build upon this foundation for higher order logic processes. This research provides a general method of leveraging cellular, mechanical metamaterials composed of conductive polymers that think about applied mechanical stress. Such fundamental findings are not limited across length scales and physics based on the mathematical and kinetmatic foundations of this new digital logic framework.   

Exploring structural instabilities in ridge-reinforced soft cylinders

Fluidic soft actuators capable of highly complex deformations have emerged as an ideal platform to realize active and adaptable robotic systems. More recently, structural instabilities have been utilized in the design of soft robots to unlock novel functionalities. In this context, we explore the mechanics of soft cylinders reinforced by helical ridges that twist and extend upon inflation. Remarkably, under certain geometrical conditions, the cylinders undergo a sudden twisting instability characterized by a heterogeneous deformation of the ridges. Guided by modeling and experiments, we describe the evolution of this instability and the transition between the different deformation regimes as a function of material properties, geometrical parameters, and input volume. This novel twisting instability may open new routes towards nonlinear textured soft actuators with increased performance.   

Scalable information processing in conductive mechanical metamaterials

Engineered materials that possess the requisite functions of lifeforms are a fascinating platform that could augment societal functions and help preserve the quality of the resources in our environment. A pivotal function for autonomy is decision-making, which occurs at a range of levels of advancement in nature. Researchers have fashioned rudimentary examples of intelligence in engineered material systems, such as by forming the basis for AND and OR logic operations in stimuli-responsive materials. Yet, the rate of computation and complexity of operations achievable are both limited by the frameworks and materials that are considered. This presentation describes a scalable means for sequenced combinational logic operations in conductive mechanical metamaterials that facilitates rapid processing of addition, subtraction, and multiplication operations: the core of modern computing. The method exploits a new bridge among mathematics, switchable Boolean circuits, and kinematics, and realizes the computing material systems using conductive polymer networks applied to reconfigurable mechanical metamaterials. Following a detailed description of the underlying mathematical design approach, the utilization of the decision-making materials is exemplified underscoring the near-immediate rate of information processing. The next steps of research are described to help bridge this concept of decision-making to autonomous, soft matter.   

Teaching multifunctionality to nonlinear fluidic networks

Soft robots powered by pressurized fluid are enabling a variety of innovative applications in diverse areas, from biomimetics to rehabilitation. Such soft machines need suitable controllers. Currently, there is no general design strategy for building non-electronic control modules that require few inputs yet enable multiple functionalities.

Here, we demonstrate a fluidic network that acts as just such a multifunctional control device. Crucially, the network structure is designed via a simple computational algorithm, based on recently explored contrastive learning in complex networks. This work presents a practical way to design soft robotic controllers with minimal prior knowledge.   

Inverse design of nonlinear response in flexible mechanical metamaterials

From wearable devices and energy-absorbing systems to footwear and soft robots, many applications would benefit from the inverse design of materials with a target non-linear mechanical response. Here, we present a framework to design flexible mechanical metamaterials with target nonlinear behavior. Our starting point is a metamaterial based on hinged rotating squares, which has recently attracted significant interest as it displays effective negative Poisson's ratio and supports the propagation of solitary pulses. We first show that a wide range of mechanical responses can be engineered by altering the shape of the quadrilateral units. Then, we use neural networks to learn the relationship between structure and mechanical response and combine them with an evolutionary approach to inverse design configurations with target non-linear stress-strain behaviors.   

Designing complex responses in smart structures

Coming up with increasingly smart robotic structures requires computationally solving elastic inverse problems; letting an algorithm find a geometry that results in the desired mechanical response. These approaches are limited by our ability to describe the desired structural performances, i.e. tell the inverse algorithm what we want our structure to do. For example, if we describe the desired behaviour using an elasticity tensor, we will be limited to linear-elastic structures — no matter our computational resources and the quality of our inverse algorithms. Overcoming this limitation requires coming up with novel ways to describe structural performances. In this talk, I will present two approaches towards designer structures with advanced responses. In the first approach, that we call design by code, the desired behavior is expressed as a source code in a 'structural programming language'. In the second approach, called design by data, the desired behaviour is described by a set of examples of desirable and undesirable responses. These approaches allow unprecedented structural performances ranging from the realisation of a fully mechanical 8-bits CPU, to metamaterials that selectively react to verbal commands.   

Architected metamaterials for routing nonlinear mechanical pulses

Actuation, locomotion, and sensing of robotic systems are just some of the key functionalities that can be enhanced by the efficient control of nonlinear mechanical waves in mechanical metamaterials. Within this context, we focus on the design of flexible mechanical metamaterials to route nonlinear pulses along target, arbitrary paths. We show that optimal architectures can be identified via an inverse design approach powered by the automatic differentiation of the forward nonlinear dynamic problem. The robustness of the optimal systems is then analyzed with respect to mechanical inputs of different amplitudes. The outcome is a strongly nonlinear metamaterial with potential for, for instance, propulsion in soft robotics, energy harvesting, mechanical logic, and controlled energy absorption.   

Contact force estimation from deformation of surface

Soft manipulators and interfaces are studied in various areas including human-robot systems. These soft interfaces can be used in sensing, moving, and grabbing objects. In our project, we are aiming to design 3D surface for object manipulation with stretchable materials such that it can move and lift objects with soft inflatable membrane interfaces. The surface will be designed with inflatable membrane and electrostatic clutches. Electrostatic clutches act to change stiffness of membrane and maintaining shapes under applied forces. As a result, we expect that membrane will be able to form various type of surfaces using these clutches. To estimate applied force from objects at the interface, we want to set up an algorithm to calculate force from surface deformation. Knowing the fact that energy of deformed surface can be measured by surface curvature or via discrete bending and stretching energy estimation from mass and spring network models, we have developed algorithms for simulating contact force from surface deformation to control the shape at real-time for stretchable membrane.   

Grasping via Entanglement

We present a robotic grasping strategy for complex shapes via the collective entanglement of and by an array of actuated filaments. The basic unit of this array is a slender hollow elastomeric filament that is pneumatically actuated to form a highly curved structure. The multiple self and mutual contact interactions between the filaments and a target object create a randomly tangled spatial assemblage that enables a soft conformable grasp. We demonstrate that a collective of highly compliant filamentous actuators is capable of a soft, adaptable grasp across a range of loads that vary in size, shape, and geometric and topological complexity without any feedback. A theoretical framework for the collective mechanics of filaments in contact with complex objects allows us to explain our experimental findings, while a phase diagram characterizes the design space in terms of the properties of the gripper and the target. Overall, our  grasping approach adapts to the mechanical, geometric, and topological complexity of target objects via an uncontrolled, spatially distributed, and heterogeneous scheme without perception or planning, in sharp contrast with current deterministic feedback-driven robotic grasping methods.   

Metarpillar: Soft Robotic Locomotion Based on Buckling-Driven Elastomeric Metamaterials

Mechanical instabilities are emerging as novel actuation mechanisms for the design of biomimetic soft robots and smart structures. The present study shows that by coupling buckling-driven elastomeric auxetic modules actuated by a negative air-pressure, a novel metamaterial-based caterpillar can be designed—the Metarpillar. Following a detailed analysis of the caterpillar’s locomotion, we were able to mimic both its crawling movement and locomotion by using the unique isometric compression of the modules and properly programing the anterograde modular peristaltic contractions. The bioinspired locomotion of the Metarpillar uses the bending triggered by the buckling-driven module contraction to control the friction through a dynamic anchoring between the soft robot and the surface, which is the main mechanism for locomotion in caterpillars and other crawling organisms. Thus, the Metarpillar not only mimics the locomotion of the caterpillar but also displays dynamic similarity and equivalent, or even faster, speeds. Our approach based on metamaterial buckling actuator units opens up a novel strategy for biomimetic soft robotic locomotion that can be extended beyond caterpillars.   

Bi-shell valve inspired by shell snapping interaction for rapid actuation of soft pneumatic actuators

Delivering rapid motion to a soft pneumatic robot is challenging. So far, existing concepts have relied on the use of either pressure control strategies, chemical explosions embedded into the soft robot body as power source, or structural elements that harness elastic instabilities. In this work, we introduce a bi-shell valve that can offer rapid deflation to soft actuators under volume-controlled conditions and without necessarily need to modify the architecture of the soft robot. The design of the bi-shell valve is inspired by the snapping and interaction of the constituent elastic shells, a hemispherical shell with a large geometric defect and a spherical cap. Upon deflation, the former first stores a sizeable amount of volume change and elastic energy, which are then suddenly released upon the snapping of the latter. By tuning shell geometry and material property, the snapping of the valve can be effectively programmed for target applications. The bi-shell valve along with its two variations for rapid inflation valve and pneumatic volume fuse extends the capabilities of existing strategies to supply fast actuation to soft pneumatic robots.   

Exploiting Geometrical Frustration in Multistable Soft Robots Part 1: Controlled Underactuation

Leveraging instabilities offers exciting opportunities to simplify the actuation of soft robots. A key roadblock for the widespread adoption of soft robotics lies in the difficulty of commanding desired kinematic configurations, a process that often requires sensor arrays and complex closed-loop control. We present a class of soft robots with encoded multiple accessible, stable states that provide a route to shape reconfiguration without closed-loop control. Informed by the mechanics of hierarchically multistable metastructures, we design coexisting states resembling different actuation modes in soft manipulators, including grasping and twisting. We exploit the presence of geometrical frustration to access such functional global states using a limited number of actuators and primitive open-loop control. This is achieved by leveraging distinct spatiotemporal inversion sequences to access desired coexisting states on-demand.  Our strategy offers a new route for controlling soft multistable robots exploiting their strong nonlinear mechanics to the designer’s advantage.     

An active asymmetric surface as the simplest soft locomotor

Soft robots, owing to their inherent compliance, hold the promise of adapting to different environments for effortless locomotion; however they typically require complex actuation sequences and bulky mechanisms, often resulting in low traveling speeds and limited action radii. Here, we introduce a soft, active surface that combines symmetric vibrations with asymmetric geometric elements to achieve propulsion. We present a model that captures the fundamental elastic behaviour of the asymmetric feature, showing that a non-trivial 2D motion emerges from the interaction between the vibration, gravity, elasticity and friction. We also present an experimental validation of our predictions, combining a silicone sawtooth-patterned surface with a vibrating source and achieving traveling speeds of 45 mm/s (0.75 bodylengths/second) on smooth surfaces. This active soft surface could then be added as a propelling module to soft robots, or it can function as a self-standing locomotor, and more complex functionalities could be achieved by combining multiple units or implementing shape-morphing designs (e.g. based on origami and kirigami).