This paper presents the key principles of eViper-2D - a thin large-area soft robotics platform - as a new development of the previous extendable Vibrating Intelligent Piezo-Electric Robot (eViper) platform. We first introduce the mechanical, electrical, and control framework of eViper-2D, and then develop systematic and scalable methods to study the impact of diverse actuation patterns on robotic motion dynamics and energy efficiency. By integrating power electronics, communication circuits, piezoelectric actuators, and batteries onboard, the eViper-2D platform enables rapid design iteration and quick evaluation of different control strategies for the multi-actuator soft robot. The platform supports data-driven modeling via automated data acquisition. We show that eViper-2D can provide rich insights into optimizing actuation patterns to achieve agile motion and minimal cost of transport (COT).

Electrically-driven soft robots based on piezoelectric actuators may enable compact form factors and maneuverability in complex environments. In most prior work, piezoelectric actuators are used to control a single degree of freedom. In this work, the coordinated activation of five independent piezoelectric actuators, attached to a common metal foil, is used to implement inchworm-inspired crawling motion in a robot that is less than 0.5 mm thick. The motion is based on the control of its friction to the ground through the robot's shape, in which one end of the robot (depending on its shape) is anchored to the ground by static friction, while the rest of its body expands or contracts. A complete analytical model of the robot shape, which includes gravity, is developed to quantify the robot shape, friction, and displacement. After validation of the model by experiments, the robot's five actuators are collectively sequenced for inchworm-like forward and backward motion.

Electrostatic actuators provide a promising approach to creating soft robotic sheets, due to their flexible form factor, modular integration, and fast response speed. However, their control requires kilo-Volt signals and understanding of complex dynamics resulting from force interactions by on-board and environmental effects. In this work, we demonstrate an untethered planar five-actuator piezoelectric robot powered by batteries and on-board high-voltage circuitry, and controlled through a wireless link. The scalable fabrication approach is based on bonding different functional layers on top of each other (steel foil substrate, actuators, flexible electronics). The robot exhibits a range of controllable motions, including bidirectional crawling (up to ~0.6 cm/s), turning, and in-place rotation (at ~1 degree/s). High-speed videos and control experiments show that the richness of the motion results from the interaction of an asymmetric mass distribution in the robot and the associated dependence of the dynamics on the driving frequency of the piezoelectrics. The robot's speed can reach 6 cm/s with specific payload distribution.

Soft robots present unique capabilities, but have been limited by the lack of scalable technologies for construction and the complexity of algorithms for efficient control and motion. These depend on soft-body dynamics, high-dimensional actuation patterns, and external/onboard forces. This paper presents scalable methods and platforms to study the impact of weight distribution and actuation patterns on fully untethered modular soft robots. An extendable Vibrating Intelligent Piezo-Electric Robot (eViper), together with an open-source Simulation Framework for Electroactive Robotic Sheet (SFERS) implemented in PyBullet, was developed as a platform to analyze the complex weight-locomotion interaction. By integrating power electronics, sensors, actuators, and batteries onboard, the eViper platform enables rapid design iteration and evaluation of different weight distribution and control strategies for the actuator arrays. The design supports both physics-based modeling and data-driven modeling via onboard automatic data-acquisition capabilities. We show that SFERS can provide useful guidelines for optimizing the weight distribution and actuation patterns of the eViper, thereby achieving maximum speed or minimum cost of transport (COT).

Soft robots have drawn great interest due to their ability to take on a rich range of shapes and motions, compared to traditional rigid robots. However, the motions, and underlying statics and dynamics, pose significant challenges to forming well-generalized and robust models necessary for robot design and control. In this work, we demonstrate a five-actuator soft robot capable of complex motions and develop a scalable simulation framework that reliably predicts robot motions. The simulation framework is validated by comparing its predictions to experimental results, based on a robot constructed from piezoelectric layers bonded to a steel-foil substrate. The simulation framework exploits the physics engine PyBullet, and employs discrete rigid-link elements connected by motors to model the actuators. We perform static and AC analyses to validate a single-unit actuator cantilever setup and observe close agreement between simulation and experiments for both the cases. The analyses are extended to the five-actuator robot, where simulations accurately predict the static and AC robot motions, including shapes for applied DC voltage inputs, nearly-static “inchworm” motion, and jumping (in vertical as well as vertical and horizontal directions). These motions exhibit complex non-linear behavior, with forward robot motion reaching ̴1 cm/s. Our open-source code can be found at: https://github.com/zhiwuz/sfers.

In the development of human-centric systems, access to a large number of human information signals is required. Such signals can be acquired from both ambient and on-person (wearable) sensors. Large-area electronics (LAE) provide distinct capabilities for creating the required diverse, distributed and conformal sensors. However, the large volume of and complex correlation to target information within the captured data requires significant processing and inference. This makes an LAE-CMOS hybrid system well-suited to such applications. Interfacing between the two technologies is a challenge in hybrid system design. We demonstrate an emerging solution space based on information-processing-oriented interfaces, through two case studies: 1) an image sensing and compression system based on random projection [1]; 2) an electroencephalogram (EEG) acquisition and biomarker-extraction system using compressive-sensing circuits [2].

Large-Area Electronics (LAE) technology has enabled the development of physically-expansive sensing systems with a flexible form-factor, including large-aperture microphone arrays. We propose an approach to blind source separation based on leveraging such an array. In our algorithm we carry out delay-sum beamforming, but use frequency-dependent time delays, making it well-suited for a practical reverberant room. This is followed by a binary mask stage for further interference cancellation. A key feature is that it is fully "blind", since it requires no prior information about the location of the speakers or microphones. Instead, we carry out k-means cluster analysis, to estimate time delays in the background from acquired audio signals that represent the mixture of simultaneous sources. We have tested this algorithm in a conference room (T60 = 350 ms), using two linear arrays consisting of: (1) commercial electret capsules, and (2) LAE microphones, fabricated in-house. We have achieved high-quality separation results, obtaining a mean PESQ MOS improvement (relative to the unprocessed signal) for the electret array of 0.7 for two sources and 0.6 for four simultaneous sources, and for the LAE array of 0.5 and 0.3, respectively.

Hybrid large-area systems aim to leverage the strengths of two complementary technologies: (1) large-area electronics (LAE), which enables dense arrays of diverse transducers on substrates that can be large and flexible; and (2) silicon CMOS ICs, which enable efficient and high-performance instrumentation, computation, and power management. A key challenge in realizing these hybrid systems on a large-scale lies in the interfacing required between the two technologies. We describe methods to ease the interfacing, enabled by device, circuit, and algorithmic advances, thereby suggesting a range of challenges and opportunities that are exposed when thinking about systems.

Hybrid systems combine Large-Area Electronics (LAE) with high-performance technologies (e.g., silicon CMOS) [1]. With architectural concepts for hybrid systems broadening to match the range of emerging applications, this paper examines modular approaches for multi-sheet, multi-technology integration. It identifies the interfaces required as a critical backbone. For interfaces associated with various system functionalities (sensing, processing, powering), specific approaches are surveyed and analyzed, taking from insights derived from several previous experimental demonstrations of complete hybrid systems.

Accurate and reliable damage characterization (i.e., damage detection, localization, and evaluation of extent) in civil structures and infrastructure is an important objective of structural health monitoring (SHM). Highly accurate and reliable characterization of damage at early stages requires continuous or quasi-continuous direct sensing of the critical parameters. Direct sensing requires deploying dense arrays of sensors, to enhance the probability that damage will result in signals that can be directly acquired by the sensors. However, coverage by dense arrays of sensors over the large areas that are of relevance represents an enormous challenge for current technologies. Large area electronics (LAE) is an emerging technology that can enable the formation of dense sensor arrays spanning large areas (several square meters) on flexible substrates. This paper explores the requirements and technology for a sensing sheet for SHM based on LAE and crystalline silicon CMOS integrated circuits (ICs). The sensing sheet contains a dense array of thin-film full-bridge resistive strain sensors, along with the electronics for strain readout, full-system self-powering, and communication. Research on several stages is presented for translating the sensing sheet to practical SHM applications. This includes experimental characterization of an individual sensor's response when exposed to cracks in concrete and steel; theoretical and experimental performance evaluation of various geometrical parameters of the sensing sheet; and development of the electronics necessary for sensor readout, power management, and sensor-data communication. The concept of direct sensing has been experimentally validated, and the potential of a sensing sheet to provide direct sensing and successful damage characterization has been evaluated in the laboratory setting. A prototype of the sensing sheet has also been successfully developed and independently characterized in the laboratory, meeting the required specifications. Thus, a sensing sheet for SHM applications shows promise both in terms of practicality and effectiveness.

By enabling diverse and large-scale transducers, large-area electronics raises the potential for electronic systems to interact much more extensively with the physical world than is possible today. This can substantially expand the scope of applications, both in number and in value. But first, translation into applications requires a base of system functions (instrumentation, computation, power management, communication). These cannot be realized on the desired scale by large-area electronics alone. It is necessary to combine large-area electronics with high-performance, high-efficiency technologies, such as crystalline silicon CMOS, within hybrid systems. Scalable hybrid systems require rethinking the subsystem architectures from the start by considering how the technologies should be interfaced, on both a functional and physical level. To explore platform architectures along with the supporting circuits and devices, we consider as an application driver, a self-powered sheet for high-resolution structural health monitoring (of bridges and buildings). Top-down evaluation of design alternatives within the hybrid design space and pursuit of template architectures exposes circuit functions and device optimizations traditionally overlooked by bottom-up approaches alone.

We fabricated an array of organic LED (OLED) pixels on a dome of clear polymer foil. The array is first formed on the flat polymer substrate and then is shaped to the dome. During the shaping process, the polymer substrate and the metal interconnect undergo plastic deformation while the OLED pixels remain intact. The OLED pixels have comparable I-V characteristics before and after deformation, but the luminous efficiency was reduced by the deformation, apparently as a consequence of fractures in the aluminum cathode. The demonstration of OLED displays on a spherical surface is an important advance in the fabrication of conformally shaped electronics.

Elastic electronic surfaces will integrate stiff thin film devices onto compliant polymer substrates. These surfaces may be stretched once or many times, by up to tens of percent strain. One way to make such an elastic electronic surface is to distribute rigid subcircuit islands over the polymer surface, and then fabricate active devices on the islands. These islands need to be interconnected with stretchable metallization. We describe stretchable interconnects made of stripes of thin gold film patterned on elastomeric membranes. These membranes can be stretched by up to twice their initial length and maintain electrical conduction. We review the fabrication of these conductors, present their electrical and mechanical properties, and summarize our model for their extreme stretchability. Using such stretchable interconnects, we made the first elastic circuit, an inverter of thin film transistors. The circuit remains functional when stretched and relaxed by 12% strain.