A pneumatic random-access memory for controlling soft robots

3D-printed digital pneumatic logic for the control of soft robotic actuators

Soft robots are paving their way to catch up with the application range of metal-based machines and to occupy fields that are challenging for traditional machines. Pneumatic actuators play an important role in this development, allowing the construction of bioinspired motion systems. Pneumatic logic gates provide a powerful alternative for controlling pressure-activated soft robots, which are often controlled by metallic valves and electric circuits. Many existing approaches for fully compliant pneumatic control logic suffer from high manual effort and low pressure tolerance. In our work, we invented three-dimensional (3D) printable, pneumatic logic gates that perform Boolean operations and imitate electric circuits. Within 7 hours, a filament printer is able to produce a module that serves as an OR, AND, or NOT gate; the logic function is defined by the assigned input signals. The gate contains two alternately acting pneumatic valves, whose work principle is based on the interaction of pressurized chambers and a 3D-printed 1-millimeter tube inside. The gate design does not require any kind of support material for its hollow parts, which makes the modules ready to use directly after printing. Depending on the chosen material, the modules can operate on a pressure supply between 80 and more than 750 kilopascals. The capabilities of the invented gates were verified by implementing an electronics-free drink dispenser based on a pneumatic ring oscillator and a 1-bit memory. Their high compliance is demonstrated by driving a car over a fully flexible, 3D-printed robotic walker controlled by an integrated circuit.

Nonlinear Inflatable Actuators for Distributed Control in Soft Robots

As soft robotic systems grow in complexity and functionality, the size and stiffness of the needed control hardware severely limits their application potential. Alternatively, functionality can be embodied within actuator characteristics, drastically reducing the amount of peripherals. Functions such as memory, computation, and energy storage then result from the intrinsic mechanical behavior of precisely designed structures. Here, actuators are introduced with tunable characteristics to generate complex actuation sequences from a single input. Intricate sequences are made possible by harnessing hysteron characteristics encoded in the buckling of a cone-shaped shell incorporated in the actuator design. A large variety of such characteristics are generated by varying the actuator geometry. This dependency is mapped and used for creating a tool to determine the actuator geometry that yields a desired characteristic. Using this tool, a system with six actuators is created that plays the final movement of Beethoven's Ninth Symphony with a single pressure supply.

Feeling the beat: a smart hand exoskeleton for learning to play musical instruments

Individuals who have suffered neurotrauma like a stroke or brachial plexus injury often experience reduced limb functionality. Soft robotic exoskeletons have been successful in assisting rehabilitative treatment and improving activities of daily life but restoring dexterity for tasks such as playing musical instruments has proven challenging. This research presents a soft robotic hand exoskeleton coupled with machine learning algorithms to aid in relearning how to play the piano by 'feeling' the difference between correct and incorrect versions of the same song. The exoskeleton features piezoresistive sensor arrays with 16 taxels integrated into each fingertip. The hand exoskeleton was created as a single unit, with polyvinyl acid (PVA) used as a stent and later dissolved to construct the internal pressure chambers for the five individually actuated digits. Ten variations of a song were produced, one that was correct and nine containing rhythmic errors. To classify these song variations, Random Forest (RF), K-Nearest Neighbor (KNN), and Artificial Neural Network (ANN) algorithms were trained with data from the 80 taxels combined from the tactile sensors in the fingertips. Feeling the differences between correct and incorrect versions of the song was done with the exoskeleton independently and while the exoskeleton was worn by a person. Results demonstrated that the ANN algorithm had the highest classification accuracy of 97.13% ± 2.00% with the human subject and 94.60% ± 1.26% without. These findings highlight the potential of the smart exoskeleton to aid disabled individuals in relearning dexterous tasks like playing musical instruments.

Pneumatic computers for embedded control of microfluidics

Alternative computing approaches that interface readily with physical systems are well suited for embedded control of those systems. We demonstrate finite state machines implemented as pneumatic circuits of microfluidic valves and use these controllers to direct microfluidic liquid handling procedures on the same chip. These monolithic integrated systems require only power to be supplied externally, in the form of a vacuum source. User input can be provided directly to the chip by covering pneumatic ports with a finger. State machines with up to four bits of state memory are demonstrated, and next-state combinational logic can be fully reprogrammed by changing the hole-punch pattern on a membrane in the chip. These pneumatic computers demonstrate a framework for the embedded control of physical systems and open a path to stand-alone lab-on-a-chip devices capable of highly complex functionality.

Early career scientists converse on the future of soft robotics

During the recent decade, we have witnessed an extraordinary flourishing of soft robotics. Rekindled interest in soft robots is partially associated with the advances in manufacturing techniques that enable the fabrication of sophisticated multi-material robotic bodies with dimensions ranging across multiple length scales. In recent manuscripts, a reader might find peculiar-looking soft robots capable of grasping, walking, or swimming. However, the growth in publication numbers does not always reflect the real progress in the field since many manuscripts employ very similar ideas and just tweak soft body geometries. Therefore, we unreservedly agree with the sentiment that future research must move beyond "soft for soft's sake." Soft robotics is an undoubtedly fascinating field, but it requires a critical assessment of the limitations and challenges, enabling us to spotlight the areas and directions where soft robots will have the best leverage over their traditional counterparts. In this perspective paper, we discuss the current state of robotic research related to such important aspects as energy autonomy, electronic-free logic, and sustainability. The goal is to critically look at perspectives of soft robotics from two opposite points of view provided by early career researchers and highlight the most promising future direction, that is, in our opinion, the employment of soft robotic technologies for soft bio-inspired artificial organs.

Programmable soft valves for digital and analog control

In soft devices, complex actuation sequences and precise force control typically require hard electronic valves and microcontrollers. Existing designs for entirely soft pneumatic control systems are capable of either digital or analog operation, but not both, and are limited by speed of actuation, range of pressure, time required for fabrication, or loss of power through pull-down resistors. Using the nonlinear mechanics intrinsic to structures composed of soft materials-in this case, by leveraging membrane inversion and tube kinking-two modular soft components are developed: a piston actuator and a bistable pneumatic switch. These two components combine to create valves capable of analog pressure regulation, simplified digital logic, controlled oscillation, nonvolatile memory storage, linear actuation, and interfacing with human users in both digital and analog formats. Three demonstrations showcase the capabilities of systems constructed from these valves: 1) a wearable glove capable of analog control of a soft artificial robotic hand based on input from a human user's fingers, 2) a human-controlled cushion matrix designed for use in medical care, and 3) an untethered robot which travels a distance dynamically programmed at the time of operation to retrieve an object. This work illustrates pathways for complementary digital and analog control of soft robots using a unified valve design.

Review of Electronics-Free Robotics: Toward a Highly Decentralized Control Architecture

In recent years, conventional model-based motion control has become more challenging owing to the continuously increasing complexity of areas in which robots must operate and navigate. A promising approach for solving this issue is by employing interaction-based robotics, which includes behavior-based robotics, morphological computations, and soft robotics that generate control and computation functions based on interactions between the robot body and environment. These control strategies, which incorporate the diverse dynamics of the environment to generate control and computation functions, may alleviate the limitations imposed by the finite physical and computational resources of conventional robots. However, current interaction-based robots can only perform a limited number of actions compared with conventional robots. To increase the diversity of behaviors generated from body–environment interactions, a robotic body design methodology that can generate appropriate behaviors depending on the various situations and environmental stimuli that arise from them is necessitated. Electronics-free robotics is reviewed herein as a paradigm for designing robots with control and computing functions in each part of the body. In electronics-free robotics, instead of using electrical sensors or computers, a control system is constructed based on only mechanical or chemical reactions. Robotic bodies fabricated using this approach do not require bulky electrical wiring or peripheral circuits and can perform control and computational functions by obtaining energy from a central source. Therefore, by distributing these electronics-free controllers throughout the body, we hope to design autonomous and highly decentralized robotic bodies than can generate various behaviors in response to environmental stimuli. This new paradigm of designing and controlling robot bodies can enable realization of completely electronics-free robots as well as expand the range of conventional electronics-based robot designs.