Spectropolarimetry is a powerful technique for remote sensing of the environment. It enables the retrieval of particle shape and size distributions in air and water to an extent that traditional spectroscopy cannot. SPEX is an instrument concept for spectropolarimetry through spectral modulation, providing snapshot, and hence accurate, hyperspectral intensity and degree and angle of linear polarization. Successful SPEX instruments have included groundSPEX and SPEX airborne, which both measure aerosol optical thickness with high precision, and soon SPEXone, which will fly on PACE. Here, we present a low-cost variant for consumer cameras, iSPEX 2, with universal smartphone support. Smartphones enable citizen science measurements which are significantly more scaleable, in space and time, than professional instruments. Universal smartphone support is achieved through a modular hardware design and SPECTACLE data processing. iSPEX 2 will be manufactured through injection molding and 3D printing. A smartphone app for data acquisition and processing is in active development. Production, calibration, and validation will commence in the summer of 2020. Scientific applications will include citizen science measurements of aerosol optical thickness and surface water reflectance, as well as low-cost laboratory and portable spectroscopy.
Soft robots with many degrees of freedom, modelled after snakes or tentacles, can locomote through a combination of controlled friction and phased multi-segment deformation. Using different periodic motions (gaits) snakes (and snake-like robots) are able to cross open space, climb narrow passages, side-wind across granular substrates, and more. Unlike their biological counterparts, snake-like robots should be able to adapt easily to space flight by utilising controllable friction elements in the form of electro-adhesive pads to selectively attach to and detach from surfaces and objects. They could operate on the interior and exterior of satellites to perform maintenance and repair, or even explore the surfaces of small astronomical bodies which do not produce enough gravity to allow for traditional wheeled rovers.
Dielectric elastomer actuators (DEAs) are an ideal candidate for the driving system of such a robot, and have already demonstrated the ability to form multi-degree of freedom actuators of varying design. They are lightweight, use minimal current to maintain a given position, have high energy density, and are capable of self-sensing their strain, reducing the need for external monitoring. We present here the design and analysis of a lightweight DEA snake-like robot incorporating electro-adhesive elements for operating in zero-gravity environments, including different gait waveforms for enhanced performance and finite element analysis for design optimisation. We conclude with discussion of future improvements, such as the incorporation of dielectric elastomer switches for greater autonomy.
Hand gesture recognition algorithms require information from the material world to be converted to digital data. In this paper we present an analysis of dielectric elastomer sensors for hand gesture recognition. A glove with five dielectric elastomer sensors has been used to collect motion data from the hand. The capacitance value of each sensor was read and analysed for a total of 24 participants. The study shows that the sensors provide enough information to differentiate gestures from each participant, although the maximum capacitance value varied with each participant, making gesture recognition over all participants difficult. Data processing allowed for this problem to be solved.
The behaviour of Dielectric Elastomer Actuators (DEA) can be predicted using hyperelastic models that are based on strain energy density functions. The parameters used in the hyperelastic models are generally obtained via a uni-axial pull test. However, DEAs are most commonly used in an biaxially stretched configuration. This is an appropriate assumption if the modelled parameters translate accurately to different stretch configurations. We have conducted stress-stretch experiments on silicone membranes in two different configurations; uni-axial and pure shear stretch. Fitting common hyperelastic models, such as Gent, to the experimental data shows that the modelling parameters depend on the stretch configuration. In addition, we show that the Mullins effect, where the stress-stretch response is dependent on the maximum stretch previously experienced by the sample, is predominant in the silicone membranes. This means that the model parameters depend on the loading configuration and the stretch history of the sample making it difficult to predict the behaviour of highlyprestretched DEAs. One way to tackle this issue is to carry out testing as close to the original configuration as possible which is difficult in the case of highly prestretched DEAs. We have created a model that takes into account both the loading configuration and the Mullins effect and used this to optimize the prestretch and stretch of the cell stretching device.
Biofouling accumulation on synthetic underwater surfaces presents serious economic problem for the marine industry. When a substrate-bonded dielectric elastomer (DE) is subjected to high voltage, deformations in form of creases can be formed at the surface of the DE. This deformation, has been already demonstrated for the prevention and detachment of biofouling from the surface of DEs. In this work, we add sensing capability to the anti-biofouling effect of active DE surfaces. A device consisting of a metallic plate, a Kapton sheet, and a thin silicone membrane is immersed in conductive solution, which acts as one electrode, with the metal plate being the second electrode. Two different conductive solutions were used 3.5 wt% NaCl and 20 wt% NaCl. The surface deformation of the silicone as a function of applied voltage is monitored under microscope in order to verify electrical measurements. Breakdown measurements of the dielectric material in different conductive solutions are also performed. Because the membrane is made from incompressible elastomer and bonded to a rigid substrate, voltages below the creasing threshold create no deformation in the membrane, and therefore no change in capacitance. Above the voltage threshold, creasing instabilities appear at the surface of the silicone, thus increasing the capacitance of the device. Therefore, the capacitance of the sensor is measured as a function of applied voltage, and the voltage at which the capacitance increases is the threshold voltage at which creases occur. Creases are identified when using both 3.5 wt% NaCl and 20 wt% NaCl as top electrode. Theoretical values of creasing voltage deviate from the experimental measurements. Type of conductive solution is shown to have no significant influence on a breakdown voltage.
In this paper, we demonstrate a soft, flexible and stretchable dielectric elastomer (DE) capacitive compression mat, which is able to measure pressure/force and locations (multi-touch) simultaneously. This compression mat is composed of a multi-layer soft and stretchy DE sensor. This newly designed compression mat can be intergraded into robotic grippers to measure the grasping force and identify the contact points when picking up an object. It can also be used as a clinical measurement mat to help foot exercise treatments for diabetic patients’ ulcerated feet.
Dielectric elastomer switches have shown large potential for integrating signal processing directly into multifunctional dielectric elastomers. Previously presented continuum dielectric elastomer switches (cDES) utilize percolation effects within piezoresistive membranes to directly switch high voltages, controlling dielectric elastomer actuators. The here presented geometric dielectric elastomer switches (gDES) use geometric air gaps in encapsulated soft sensor structures to switch both high and low voltages.
gDES consist only of soft materials such as silicones and carbon-doped conductive silicones. The structured conductive electrode areas are arranged in such a way that they create small gaps within a shielded cavity. The gap can be opened or closed by an external deformation or pressure. Depending on the electrode design and mechanical characteristics, the necessary amount of deformation and pressure can be tailored exactly to the requirements of the application. Arrays of these switches can be integrated in soft robotic grippers and extend the features of those grippers by touch and shear force detection. Furthermore, gDES can act as limit switches and can be introduced in automation technology. One of the key advantages is that the switches themselves are entirely shielded and not affected by environmental influences.
gDESs have an advantage of operation at lower voltages than related cDES. This reduces the necessary amount of driving voltage and opens up the application in classic automation technologies and robotics. gDESs possess conductive silicone composites containing conductive fillers. The switching points and the general behaviour (normally-open [NO] or normally-closed [NC]) are tuned by the geometry of conductive parts associated with the shielding silicone structures. Related to percolation-based cDESs, the gDESs are produced by classic microelectronic production technologies, such as soft lithography.
We present the principle design of different gDESs and arrays of the same, the production techniques and first results of distributed touch sensing for soft robotic grippers. Methods and design parameters for adjusting the switching characteristics are presented and experimentally evaluated.
Inkjet material deposition is a promising approach to print multiple functional components for dielectric elastomer (DE) devices. The automatic fabrication process promotes reliable and repeatable results, and allows scaling to a few millimetres, which is advantageous in areas such as microfluidics and optics. We present here the printing and evaluation of novel ink formulae comprising silicone and a conductive filler. Carbon black, the conductive filler, is a popular electrode material. Although it has a relatively high resistance, it has been shown to produce compliant electrodes of good performance for dielectric elastomer actuators (DEA). Carbon black is added to liquid silicone rubber and solvents in order to obtain a solution that can be inkjet-printed. The silicone provides binding of the carbon particles into a soft matrix as well as bonding to the elastomer membrane on which it is printed. Each ink has unique electromechanical properties, e.g. sheet resistances ranging from a few kΩ/sq to MΩ/sq. We can apply different inks to provide conductive electrodes for DEA or piezoresistive components such as the dielectric elastomer switch (DES) - able to locally control charge over DEA - or simple resistor and electrode tracks. We discuss ink behaviours and printed sample components for networks of DEA and combined driving circuitry, all with soft, flexible materials.
We present an approach for evaluating the design of Dielectric Elastomer (DE) capacitive pressure sensors on robotic graspers. This approach has used the ANSYS software for Finite Element Method (FEM), along with a MatLab script for calculation of capacitance change. The model has been set up with an axisymmetric indenter and frictionless contact. This study has compared several structured dielectric elastomer (DE) pressure sensors with different sub-surface soft padding thicknesses.
The results suggest that:
-For padding that is too thin the contact area will be small with localized compression and sensor sensitivity will be compromised by this;
-For padding that is very thick compared with the sensor thickness –deformation will be spread over a wider area and the signal sensitivity will be somewhat lower; for a given indenter radius of curvature;
-This suggests that there will be an optimal padding thickness for a given contact geometry.
The approach developed and presented in the paper will be helpful for sensor soft sensor design for different applications, such as robotics and bio-instrumentational systems, in particular, the design of graspers to identify and pick up different objects.
Dielectric Elastomer Transducers (DETs) integrated into inflatable structures can form the basis for soft, low mass robots. Such robots will have very high packaging efficiency and be simple to deploy. These attributes, combined with the high power density of DETs make them ideal for space robots. In this paper we present a study of different motions achieved from the actuation of three distinct simple experimental designs. Firstly, the dome actuator constructed from a sheet of silicone rubber with segmented electrodes. Secondly, an elongation of the former, capable of producing locomotory motion from phased actuation of segments. Finally, a rolled cylindrical design varying the seam geometry, and electrode position and composition to produce different resonant and non-resonant motion. This study is comprised of experimental results, and finite element modelling of each design using commercially available FEM software. The different structures are simulated undergoing inflation and actuation, and the results compared to experimental data. Modal analyses of the inflated cylindrical structures are also compared with the frequency responses of the experimental models. Extrapolation of these basic units to more complex structures, designed to complement or replace existing space equipment, is presented for discussion alongside the remaining challenges.
We present a method for the patterning of compliant electrodes for dielectric elastomer actuators (DEA) using drop-on-demand (DoD) printing and a lift-off process. DoD is a very appealing method for the patterning of electrodes, due to its high resolution, and the design versatility brought by printing from computer files. However, it has very narrow requirements regarding the viscosity, surface tension, and agglomeration size of the solution to be printed, and a new jetting waveform must be developed for each ink. This makes experimenting with new compliant electrode formulations difficult and time-consuming. Our approach consists in printing a watersoluble sacrificial layer on the elastomer, which serves as a mask selectively protecting portions of the membrane. Compliant electrodes can then be applied on the mask by different means (brush, spray coating, stamping etc.), and the mask can subsequently be dissolved to wash away the excess of ink and reveal the pattern, similar to a lift-off process. The inkjet printing process must only be developed and optimized for a single solution (the sacrificial layer), whereas many different electrodes formulations can then rapidly be patterned and tested, without having to meet the requirements of the printer regarding viscosity, surface tension or agglomeration size. We demonstrate the method by patterning an Polyvinylpyrrolidone (PVP) mask. We then use an airbrush to apply a carbon black/silicone mixture over the whole membrane. Finally, we wash away the mask to reveal the compliant electrodes.
We present a simple open-loop method to suppress the viscoelastic drift of dielectric elastomer actuators (DEAs). Viscoelastic creep is one of the drawbacks of DEAs, especially when made with acrylic elastomer membranes (VHB). This leads to a time-dependent strain response to a voltage input, thus making the precise control of DEAs difficult. Closed-loop methods can be used to mitigate this issue, but they require additional sensors for the strain feedback, or a complex power supply if capacitive self-sensing is used. Our method is based on quasilinear viscoelasticity and relies on two simple characterisation tests: 1) a slow voltage ramp to characterise the steady-state strain versus voltage behaviour, and 2) a strain versus time response to a voltage step input. The model then enables to calculate the voltage profile required to obtain a target strain output. A simple analytical expression can be used to generate strain step responses. The method enables to suppress the viscoelastic drift and to increase the response speed of DEAs. To obtain arbitrary strain profiles (sinusoid, square, etc.), the required voltage can be numerically calculated, thus making the method a simple and versatile tool to compensate the viscoelasticity, and generate precise strain profiles from DEAS, without the need for closed-loop operation.
Networks of soft wearable stretch sensors offer a distinctive advantage over camera based motion capture systems, since they can operate outside studios or laboratories. Soft sensors can be placed tightly against the skin, and are therefore capable of detecting soft tissue deformation, which is essential for reconstructing natural motion. However, the large number of sensors necessary to capture multiple limbs at a high enough spatial resolution requires many non-stretchable wires and rigid connectors, which severely compromise user comfort. In previous work, we have demonstrated how the wiring can be minimised in soft capacitive stretch sensing. Multiple sensors were interconnected with fixed external resistors along a R-C transmission line, which allowed capacitances to be measured through a single channel. We have now taken a similar approach towards resistive stretch sensors that change their resistance under deformation. The proposed method is based on a sensing transmission line consisting of resistive stretch sensors and fixed capacitors. The transmission line impedance was measured by applying excitation voltages with different frequencies. A system of nonlinear equations was established from measured and mathematically modelled transmission line resistances, and solved numerically for the unknown sensor resistances. Measuring multiple sensor resistances through one channel reduces the number of wires and connector, and potentially leads to a smaller circuit board footprint.
Accurately capturing human motion underwater has potential applications in diver health monitoring, human- machine interaction and performance sport coaching. Unfortunately the human body has approximately 200 bones and 600 skeletal muscles giving rise to a broad range of degrees of freedom. To effectively capture this movement with dielectric elastomer sensors a substantial network is required. One often overlooked challenge is the connection between the dielectric elastomer sensor and central electronics. On land this is as simple as wires connecting the two. Underwater however, especially when considering a network of sensors, this becomes a more complicated task.
In the proposed method parallel plate capacitors are used to transfer power across the encapsulation layer to the sensor, removing any need for protruding wires or cable glands. With one electrode placed within the encapsulation and the second connected to the sensor, sensors are replaceable even underwater. To maintain sensor performance however, a relatively high capacitance is required. For example if the coupling capacitance is 20x greater than sensor capacitance, sensitivity is reduce by approximately 20%. Whereas if the coupling capacitance is only 10x greater, sensitivity is reduced by 40%. Due to these high capacitance requirements combined with the area and weight restrictions of wearable applications, we have investigated the practicality of implementing capacitive coupling. A capacitive coupling interface has been developed and tested with dielectric elastomer sensors underwater. Analysis of the interface's impact on sensor sensitivity, measurement electronics and overall coupling capacitor size is presented.
Multi touch sensors are widely used for screen interfaces, but are at an early stage of development for soft wearable technology and humanoid devices. We demonstrated a soft, flexible and stretchable tactile dielectric elastomer (DE) capacitive sensor array which is designed for multi-touch applications. The touch input is measured by the capacitance variation resulting from the deformation of the sensor modelled as a variable parallel plate capacitor. The flexibility and soft nature of capacitive DE sensor makes them comfortable to wear and versatile. This sensor module is composed of a 2-D capacitive sensor array composed of a grid of DE sensors. The sensor arrangement enables the measurement of touch capacitance on and between sensor centerlines. This technology has fewer connections with fewer wires and enables continuous location identification; convenient for emerging wearable technology as well as humanoid devices. It is possibility solution for wearable technology that needs to measure the reaction of forces in the human body; and can also be applicable to measure/control in humanoid devices to determine grasp ability to pick up an object.
Dielectric elastomer generators (DEG) are well suited to harvest energy from natural motion sources (e.g. water, human locomotion). DEG require a source of high voltage charge to generate energy. In low cost, low power DEG, a high voltage charge source is expensive and impractical to implement. The Self Priming Circuit (SPC) can be used to remove the high voltage charge source and replace it with a low voltage one. The SPC works by moving charge onto and off the DEG in synchrony with DEG compression to enable voltage boosting. For the initial cycle a low voltage source is still required in the form of a battery or similar device which in some instances can completely discharge, rendering the DEG useless. Another approach is to include an electret into the DEG design. The electret acts as a permanent voltage source for the DEG and SPC. This allows the DEG to receive a medium voltage (much higher than a battery) from the electret and then boost this voltage up to a high voltage where generation efficiency is improved. This paper presents an integrated SPC with an electret charge source that is capable of boosting quickly to a high voltage without the addition of external charge.
Conventional electronics are typically rigid, introducing unwanted stiffness to otherwise entirely soft systems. Emerging soft and stretchable electronics provide a platform for integrating driving electronics in soft robotics and structures. A stretchable electrode having strain-dependent resistance is the dielectric elastomer switch (DES). The DES enables direct control of artificial muscles, or dielectric elastomer actuators (DEA), a popular material in soft robotics. Electromechanically interacting DEA and DES together make up smart actuator networks, with the DES as piezoresistive-charge gates. The DES is a unique stretchable electrode in that it directly couples mechanical strain with a logic state change. We have previously demonstrated logic gates and memory elements using DES/DEA arrays. Performance, particularly speed and cycle life, were limited due largely to acrylic-based, viscoelastic materials and hand-made fabrication process. Here we present computing elements with enhanced performance, comprising silicone membranes and airbrushed silicone-based electrodes. We also demonstrate a new model - a dielectric elastomer digital oscillator. The oscillator provides the timing signal for sequential logic elements, which reduces number of wires and inputs needed for DE circuits. Finally, we also use the mechanosensitive DES to implement adjustable frequency of the DE oscillators.
Multifunctional Dielectric Elastomer (DE) devices are well established as actuators, sensors and energy har- vesters. Since the invention of the Dielectric Elastomer Switch (DES), a piezoresistive electrode that can directly switch charge on and off, it has become possible to expand the wide functionality of DE structures even more. We show the application of fully soft DE subcomponents in biomimetic robotic structures.
It is now possible to couple arrays of actuator/switch units together so that they switch charge between them- selves on and off. One can then build DE devices that operate as self-controlled oscillators. With an oscillator one can produce a periodic signal that controls a soft DE robot – a DE device with its own DE nervous system. DESs were fabricated using a special electrode mixture, and imprinting technology at an exact pre-strain. We have demonstrated six orders of magnitude change in conductivity within the DES over 50% strain. The control signal can either be a mechanical deformation from another DE or an electrical input to a connected dielectric elastomer actuator (DEA). We have demonstrated a variety of fully soft multifunctional subcomponents that enable the design of autonomous soft robots without conventional electronics. The combination of digital logic structures for basic signal processing, data storage in dielectric elastomer flip-flops and digital and analogue clocks with adjustable frequencies, made of dielectric elastomer oscillators (DEOs), enables fully soft, self-controlled and electronics-free robotic structures.
DE robotic structures to date include stiff frames to maintain necessary pre-strains enabling sufficient actuation of DEAs. Here we present a design and production technology for a first robotic structure consisting only of soft silicones and carbon black.
Electromechanically coupled dielectric elastomer actuators (DEAs) and dielectric elastomer switches (DESs) may form digital logic circuitry made entirely of soft and flexible materials. The expansion in planar area of a DEA exerts force across a DES, which is a soft electrode with strain-dependent resistivity. When compressed, the DES drops steeply in resistance and changes state from non-conducting to conducting. Logic operators may be achieved with different arrangements of interacting DE actuators and switches. We demonstrate combinatorial logic elements, including the fundamental Boolean logic gates, as well as sequential logic elements, including latches and flip-flops. With both data storage and signal processing abilities, the necessary calculating components of a soft computer are available. A noteworthy advantage of a soft computer with mechanosensitive DESs is the potential for responding to environmental strains while locally processing information and generating a reaction, like a muscle reflex.
Diving, initially motivated for food purposes, is crucial to the oil and gas industry, search and rescue, and is even done recreationally by millions of people. There is a growing need however, to monitor the health and activity of divers. The Divers Alert Network has reported on average 90 fatalities per year since 1980. Furthermore an estimated 1000 divers require recompression treatment for dive-related injuries every year. One means of monitoring diver activity is to integrate strain sensors into a wetsuit. This would provide kinematic information on the diver potentially improving buoyancy control assessment, providing a platform for gesture communication, detecting panic attacks and monitoring diver fatigue. To explore diver kinematic monitoring we have coupled dielectric elastomer sensors to a wetsuit worn by the pilot of a human-powered wet submarine. This provided a unique platform to test the performance and accuracy of dielectric elastomer strain sensors in an underwater application. The aim of this study was to assess the ability of strain sensors to monitor the kinematics of a diver.
This study was in collaboration with the University of Auckland's human-powered submarine team, Team Taniwha. The pilot, completely encapsulated in a hull, pedals to propel the submarine forward. Therefore this study focused on leg motion as that is the primary motion of the submarine pilot. Four carbon-filled silicone dielectric elastomer sensors were fabricated and coupled to the pilot's wetsuit. The first two sensors were attached over the knee joints, with the remaining two attached between the pelvis and thigh. The goal was to accurately measure leg joint angles thereby determining the position of each leg relative to the hip. A floating data acquisition unit monitored the sensors and transmitted data packets to a nearby computer for real-time processing. A GoPro Hero 4 silver edition was used to capture the experiments and provide a means of post-validation. The ability of the sensors to measure joint angles was assessed by examining GoPro footage in the image processing software, ImageJ.
This paper applies dielectric elastomer sensor technology to monitoring the leg motion of a diver. The experimental set-up and results are presented and discussed.
Dielectric Elastomer Generators (DEG) can capture energy from natural movement sources such as wind, the tides and human locomotion. The harvested energy can be used for low power devices such as wireless sensor nodes and wearable electronics. A challenge for low power DEG is overcoming the losses associated with charge management. A circuit which can do this exists: the Self Priming Circuit (SPC) which consists of diodes and capacitors. The SPC is connected in parallel to the DEG where it transfers charge onto/o_ the DEG based on changes in the DEG capacitance. Modelling and experimental validation of the SPC have been performed in the past, allowing design and implementation of effective SPCs which match a particular DEG. While the SPC is effective, it is still an external circuit which adds additional mass and cost to the DEG. By splitting the DEG into separate capacitors and using them to build an SPC, the Integrated SPC (I-SPC) can be realized. This reduces the components required to build a SPC/DEG and improves the performance. This paper presents a mathematical model with experimental data of a first order I-SPC. Additionally, comparisons between the SPC and I-SPC are drawn.
“Soft, stretchable, and unobtrusive”. These are some of the attributes frequently associated with capacitive dielectric elastomer (DE) sensors for body motion capture. While the sensors themselves are soft and elastic, they require rigid peripheral components for capacitance measurement. Each sensor is connected to a separate channel on the sensing circuitry through its own set of wires. In wearable applications with large numbers of sensors, this can lead to a considerable circuit board footprint, and cumbersome wiring. The additional equipment can obstruct movement and alter user behaviour. Previous work has demonstrated how a transmission line model can be applied to localise deformation on a single DE sensor. Building on this approach, we have developed a distributed sensing method by arranging capacitive DE sensors and external resistors to form a transmission line, which is connected to a single sensing channel with only one set of wires. The sensors are made from conductive fabric electrodes, and silicone dielectrics, and the external resistors are off-the-shelf metal film resistors. Excitation voltages with different frequencies are applied to the transmission line. The lumped transmission line capacitances at these frequencies are passed on to a mathematical model that calculates individual sensor capacitance changes. The prototype developed for this study is capable of obtaining separate readings for simultaneously stretched sensors.
Soft and stretchy dielectric elastomer (DE) sensors can measure large strains on robotic devices and people. DE strain measurement requires electric energy to run the sensors. Energy is also required for information processing and telemetering of data to phone or computer. Batteries are expensive and recharging is inconvenient. One solution is to harvest energy from the strains that the sensor is exposed to. For this to work the harvester must also be wearable, soft, unobtrusive and profitable from the energy perspective; with more energy harvested than used for strain measurement. A promising way forward is to use the DE sensor as its own energy harvester. Our study indicates that it is feasible for a basic DE sensor to provide its own power to drive its own sensing signal. However telemetry and computation that are additional to this will require substantially more power than the sensing circuit. A strategy would involve keeping the number of Bluetooth data chirps low during the entire period of energy harvesting and to limit transmission to a fraction of the total time spent harvesting energy. There is much still to do to balance the energy budget. This will be a challenge but when we succeed it will open the door to autonomous DE multi-sensor systems without the requirement for battery recharge.
Wearable assistive devices are the future of rehabilitation therapy and bionic limb technologies. Traditional electric, hydraulic, and pneumatic actuators can provide the precise and powerful around-the-clock assistance that therapists cannot deliver. However, they do so in the confines of highly controlled factory environments, resulting in actuators too rigid, heavy, and immobile for wearable applications. In contrast, biological skeletal muscles have been designed and proven in the uncertainty of the real world. Bioinspired artificial muscle actuators aim to mimic the soft, slim, and self-sensing abilities of natural muscle that make them tough and intelligent. Fluidic artificial muscles are a promising wearable assistive actuation candidate, sharing the high-force, inherent compliance of their natural counterparts. Until now, they have not been able to self-sense their length, pressure, and force in an entirely soft and flexible system. Their use of rigid components has previously been a requirement for the generation of large forces, but reduces their reliability and compromises their ability to be comfortably worn. We present the unobtrusive integration of dielectric elastomer (DE) strain and pressure sensors into a soft Peano fluidic muscle, a planar alternative to the relatively bulky McKibben muscle. Characterization of these DE sensors shows they can measure the full operating range of the Peano muscle: strains of around 18% and pressures up to 400 kPa with changes in capacitance of 2.4 and 10.5 pF respectively. This is a step towards proprioceptive artificial muscles, paving the way for wearable actuation that can truly feel its environment.
Since the late 1990’s dielectric elastomers (DEs) have been investigated for their use as sensors. To date, there have been some impressive developments: finger displacement controls for video games and integration with medical rehabilitation devices to aid patient recovery. It is clear DE sensing is well established for dry applications, the next frontier, however, is to adapt this technology for the other 71% of the Earth’s surface. With proven and perhaps improved water resistance, many new applications could be developed in areas such as diver communication and control of underwater robotics; even wearable devices on land must withstand sweat, washing, and the rain. This study investigated the influence of fresh and salt water on DE sensing. In particular, sensors have been manufactured with waterproof connections and submersed in fresh and salt water baths. Temperature and resting capacitance were recorded. Issues with the basic DE sensor have been identified and compensated for with modifications to the sensor. The electrostatic field, prior and post modification, has been modeled with ANSYS Maxwell. The aim of this investigation was to identify issues, perform modifications and propose a new sensor design suited to wet and underwater applications.
Dielectric Elastomer Generators (DEG) offer an opportunity to capture the energy otherwise wasted from human motion. By integrating a DEG into the heel of standard footwear, it is possible to harness this energy to power portable devices. DEGs require substantial auxiliary systems which are commonly large, heavy and inefficient. A unique challenge for these low power generators is the combination of high voltage and low current. A void exists in the semiconductor market for devices that can meet these requirements. Until these become available, existing devices must be used in an innovative way to produce an effective DEG system. Existing systems such as the Bi-Directional Flyback (BDFB) and Self Priming Circuit (SPC) are an excellent example of this. The BDFB allows full charging and discharging of the DEG, improving power gained. The SPC allows fully passive voltage boosting, removing the priming source and simplifying the electronics. This paper outlines the drawbacks and benefits of active and passive electronic solutions for maximizing power from walking.
When we communicate face to face, we subconsciously engage our whole body to convey our message. In telecommunication, e.g. during phone calls, this powerful information channel cannot be used. Capturing nonverbal information from body motion and transmitting it to the receiver parallel to speech would make these conversations feel much more natural. This requires a sensing device that is capable of capturing different types of movements, such as the flexion and extension of joints, and the rotation of limbs. In a first embodiment, we developed a sensing glove that is used to control a computer game. Capacitive dielectric elastomer (DE) sensors measure finger positions, and an inertial measurement unit (IMU) detects hand roll. These two sensor technologies complement each other, with the IMU allowing the player to move an avatar through a three-dimensional maze, and the DE sensors detecting finger flexion to fire weapons or open doors. After demonstrating the potential of sensor fusion in human-computer interaction, we take this concept to the next level and apply it in nonverbal communication between humans. The current fingerspelling glove prototype uses capacitive DE sensors to detect finger gestures performed by the sending person. These gestures are mapped to corresponding messages and transmitted wirelessly to another person. A concept for integrating an IMU into this system is presented. The fusion of the DE sensor and the IMU combines the strengths of both sensor types, and therefore enables very comprehensive body motion sensing, which makes a large repertoire of gestures available to nonverbal communication over distances.
We present a new sensing method that can measure the strain at different locations in a dielectric elastomer. The method
uses multiple sensing frequencies to target different regions of the same dielectric elastomer to simultaneously detect
position and pressure using only a single pair of connections. The dielectric elastomer is modelled as an RC transmission
line and its internal voltage and current distribution used to determine localised capacitance changes resulting from contact
This sensing method greatly simplifies high degree of freedom systems and does not require any modifications to the
dielectric elastomer or sensing hardware. It is demonstrated on a multi-touch musical keyboard made from a single low
cost carbon-based dielectric elastomer with 4 distinct musical tones mapped along a length of 0.1m. Loudness was
controlled by the amount of pressure applied to each of these 4 positions.
Robotic orthoses have the potential to provide effective rehabilitation while overcoming the availability and cost constraints of therapists. These orthoses must be characterized by the naturally safe, reliable, and controlled motion of a human therapist's muscles. Such characteristics are only possible in the natural kingdom through the pain sensing realized by the interaction of an intelligent nervous system and muscles' embedded sensing organs.
McKibben fluidic muscles or pneumatic muscle actuators (PMAs) are a popular orthosis actuator because of their inherent compliance, high force, and muscle-like load-displacement characteristics. However, the circular cross-section of PMA increases their profile. PMA are also notoriously unreliable and difficult to control, lacking the intelligent pain sensing systems of their biological muscle counterparts.
Here the Peano fluidic muscle, a new low profile yet high-force soft actuator is introduced. This muscle is smart, featuring bioinspired embedded pressure and soft capacitive strain sensors. Given this pressure and strain feedback, experimental validation shows that a lumped parameter model based on the muscle geometry and material parameters can be used to predict its force for quasistatic motion with an average error of 10 - 15N. Combining this with a force threshold pain sensing algorithm sets a precedent for flexible orthosis actuation that uses embedded sensors to prevent damage to the actuator and its environment.
Nearly all surface and underwater vessels are driven by screw propulsion; ideal for coupling to rotary engines and well understood after over a century of development. But most aquatic creatures use fins for swimming. Although there are sound evolutionary reasons why fish have fins and not propellers, they are nevertheless agile, fast and efficient. Although fish-like robots such as the MIT Robotuna are providing good insight into fin-based swimming there are advantages for using humans in the experimental device. Like an airplane test pilot they can write crash reports. We present preliminary observations for the human powered finned submarine: Taniwha. The sub participated in the 2nd European International Submarine races in Gosport UK where it received a trophy for “Best Non-Propeller Performance”. Two sets of Hobie Mirage fin drives fixed to the upper and lower rear surfaces of the sub are pedaled by the pilot. The pilot also has two levers at the front, one to pitch a pair of dive planes and one for yawing a large rudder. Good speed, we estimate to be greater than 6 m/s is possible with these fins although we haven’t explored their full potential. Straying too near the surface or bottom can lead to an instability, synonymous to a stall, such that control is lost. The mechanism for this will be discussed and solutions offered. Fish are 400 million years in front of us but one day we’ll catch them.
Dielectric elastomer Generator(s) (DEG) are highly suited to harvesting from environmental sources because they are
light weight, low cost, and can be coupled directly to rectilinear motions and harvest energy efficiently over a wide
frequency range. Because of these benefits, simple and low cost generators could be enabled using DEG.
Electrical energy is produced on relaxation of a stretched, charged DEG: like-charges are compressed together and
opposite-charges are pushed apart, resulting in an increased voltage. The manner in which the DEG charge state is
controlled greatly influences the amount of energy that is produced. For instance, the highest energy density ever
demonstrated for DEG is 550 mJ/g, whereas the theoretical energy density of DEG has been reported as high as 1700
mJ/g if driven close to their failure limits.
The discrepancy between realised and theoretical energy production highlights that large performance gains can be
achieved through smarter charge control that drives the generator close to its failure limits. To do so safely, we need to
be able to monitor the real-time electromechanical state of the DEG. This paper discusses the potential of self-sensing
for providing feedback on the generator’s electromechanical state. Then we discuss our capacitive self-sensing method
which we have demonstrated to track the displacement of a Danfoss Polypower generator as it was cyclically stretched
and harvested energy.
Dielectric elastomer generators (DEG) are suited for harvesting energy from low frequency and high strain natural
sources including wind, wave and human movement. The stack configuration, for instance, in which a number of layers
of DE membrane are placed one atop the other, offers a robust, compact and solid-state way for arranging the DE
material for energy harvesting during heel strike. But the end conditions at top and bottom of a stack can substantially
limit its ability to strain. Using an analytical model for compression of the stack, we have calculated thickness changes in
capacitive membranes along the stack for several cylindrical shapes. DE generators that are short and fat will have
approximately parabolic profiles with continuous reduction in layer thickness towards the middle. This will result in
higher electrical fields at the middle with greater susceptibility to breakdown. For long, thin DEG stacks, the outward
bulging will be confined to zones at the two ends with a more uniform cylindrical profile in between. The placing of
inexpensive compliant end-caps between the DEG and a rigid structure will promote more homogeneous deformation
across the active layers so that the efficacy of these layers for energy harvesting will improve.
Many devices and processes produce low grade waste heat. Some of these include combustion engines, electrical
circuits, biological processes and industrial processes. To harvest this heat energy thermoelectric devices, using the
Seebeck effect, are commonly used. However, these devices have limitations in efficiency, and usable voltage. This
paper investigates the viability of a Stirling engine coupled to an artificial muscle energy harvester to efficiently convert
heat energy into electrical energy. The results present the testing of the prototype generator which produced 200 μW
when operating at 75°C. Pathways for improved performance are discussed which include optimising the electronic
control of the artificial muscle, adjusting the mechanical properties of the artificial muscle to work optimally with the
remainder of the system, good sealing, and tuning the resonance of the displacer to minimise the power required to drive
We draw inspiration from the fish “hearing” organ, the otolith, to create a portable engineering device that can augment a
human diver’s ability to hear underwater. The otolith is an inertial displacement sensor, consisting of a dense bony mass
that acts as a reference to the surrounding sensory hair cells. The challenges in adapting the otolith into a hearing device
are discussed. For our proposed sensor, we have explored the use of capacitive sensing for measuring displacement. A
proof of concept prototype and a finite element model of the sensor are presented.
Sensing motion of the human body is a difficult task. From an engineers’ perspective people are soft highly mobile
objects that move in and out of complex environments. As well as the technical challenge of sensing, concepts such as
comfort, social intrusion, usability, and aesthetics are paramount in determining whether someone will adopt a sensing
solution or not.
At the same time the demands for human body motion sensing are growing fast. Athletes want feedback on posture and
technique, consumers need new ways to interact with augmented reality devices, and healthcare providers wish to track
recovery of a patient.
Dielectric elastomer stretch sensors are ideal for bridging this gap. They are soft, flexible, and precise. They are low
power, lightweight, and can be easily mounted on the body or embedded into clothing. From a commercialisation point
of view stretch sensing is easier than actuation or generation - such sensors can be low voltage and integrated with
This paper takes a birds-eye view of the use of these sensors to measure human body motion. A holistic description of
sensor operation and guidelines for sensor design will be presented to help technologists and developers in the space.
Hand motion is one of our most expressive abilities. By measuring our interactions with everyday objects, we can create
smarter artificial intelligence that can learn and adapt from our behaviours and patterns. One way to achieve this is to apply
wearable dielectric elastomer strain sensors directly onto the hand.
Applications such as this require fast, efficient and scalable sensing electronics. Most capacitive sensing methods use an
analogue sensing signal and a backend processor to calculate capacitance. This not only reduces scalability and speed of
feedback but also increases the complexity of the sensing circuitry.
A capacitive sensing method that uses a DC sensing signal and continuous tracking of charge is presented. The method is
simple and efficient, allowing large numbers of dielectric elastomer sensors to be measured simulatenously.
We present an analysis on the feasibility of the 3D printing technology known as Stereolithography for adaption to Dielectric Elastomer (DE) Production. We also present a method for 3D printing in two materials using Stereolithography, solving one of the main challenges identified in adapting this technology to DEs. Stereolithography is well suited to DE production because of similarities in the materials used and because of its high achievable resolution. However, DE production requires the use of two separate materials, and of soft materials, both of which are difficult with Stereolithography. Our method makes two material printing with Stereolithography possible by using multiple resin baths and an intermediary cleaning step. If the other challenges can be overcome, automatic 3D production of DEs will be possible.
As our population ages, and trends in obesity continue to grow, joint degenerative diseases like osteoarthritis (OA) are
becoming increasingly prevalent. With no cure currently in sight, the only effective treatments for OA are orthopaedic
surgery and prolonged rehabilitation, neither of which is guaranteed to succeed.
Gait retraining has tremendous potential to alter the contact forces in the joints due to walking, reducing the risk of one
developing hip and knee OA. Dielectric Elastomer Actuators (DEAs) are being explored as a potential way of applying
intuitive haptic feedback to alter a patient’s walking gait. The main challenge with the use of DEAs in this application is
producing large enough forces and strains to induce sensation when coupled to a patient’s skin.
A novel controller has been proposed to solve this issue. The controller uses simultaneous capacitive self-sensing and
actuation which will optimally apply a haptic sensation to the patient’s skin independent of variability in DEAs and
Dielectric elastomers (DEs) can theoretically operate at efficiencies greater than that of electromagnetics. This is due to their unique mode of operation which involves charging and discharging a capacitive load at a few kilovolts (typically 1kV-4kV). Efficient recovery of the electrical energy stored in the capacitance of the DE is essential in achieving favourable efficiencies as actuators or generators. This is not a trivial problem because the DE acts as a voltage source with a low capacity and a large output resistance. These properties are not ideal for a power source, and will reduce the performance of any power conditioning circuit utilizing inductors or transformers. This paper briefly explores how circuit parameters affect the performance of a simple inductor circuit used to transfer energy from a DE to another capacitor. These parameters must be taken into account when designing the driving circuitry to maximize performance.
Being able to accurately record body motion allows complex movements to be characterised and studied. This is especially important in the film or sport coaching industry. Unfortunately, the human body has over 600 skeletal muscles, giving rise to multiple degrees of freedom. In order to accurately capture motion such as hand gestures, elbow or knee flexion and extension, vast numbers of sensors are required. Dielectric elastomer (DE) sensors are an emerging class of electroactive polymer (EAP) that is soft, lightweight and compliant. These characteristics are ideal for a motion capture suit. One challenge is to design sensing electronics that can simultaneously measure multiple sensors. This paper describes a scalable capacitive sensing device that can measure up to 8 different sensors with an update rate of 20Hz.
Dielectric elastomer generators (DEG) provide an opportunity to harvest energy from low frequency and aperiodic sources. Because DEG are soft, deformable, high energy density generators, they can be coupled to complex structures such as the human body to harvest excess mechanical energy. However, DEG are typically constrained by a rigid frame and manufactured in a simple planar structure. This planar arrangement is unlikely to be optimal for harvesting from compliant and/or complex structures. In this paper we present a soft generator which is fabricated into a 3 Dimensional geometry. This capability will enable the 3-dimensional structure of a dielectric elastomer to be customised to the energy source, allowing efficient and/or non-invasive coupling. This paper demonstrates our first 3 dimensional generator which includes a diaphragm with a soft elastomer frame. When the generator was connected to a self-priming circuit and cyclically inflated, energy was accumulated in the system, demonstrated by an increased voltage. Our 3D generator promises a bright future for dielectric elastomers that will be customised for integration with complex and soft structures. In addition to customisable geometries, the 3D printing process may lend itself to fabricating large arrays of small generator units and for fabricating truly soft generators with excellent impedance matching to biological tissue. Thus comfortable, wearable energy harvesters are one step closer to reality.
We report on the use of capacitive self-sensing to operate a DEA-based tunable grating in closed-loop mode. Due to their large strain capabilities, DEAs are key candidates for tunable optics applications. However, the viscoelasticity of elastomers is detrimental for applications that require long-term stability, such as tunable gratings and lenses. We show that capacitive sensing of the electrode strain can be used to suppress the strain drift and increase the response speed of silicone-based actuators. On the other hand, VHB actuators exhibit a time-dependent permittivity, which causes a drift between the device capacitance and its strain.
Dielectric elastomer generators (DEG) are variable capacitor power generators that are a highly promising technology
for harvesting energy from environmental sources because they have the ability to work over a wide frequency range
without sacrificing their high energy density or efficiency. DEG can also take on a wide range of configurations, so they
are customizable to the energy source.
A typical generation cycle requires electrical charge to be supplied and removed from the DEG at appropriate times as it
is mechanically deformed. The manner in which the DEG charge state is controlled greatly influences energy
production. The recently developed self-priming circuit can provide this functionality without any active electronics, but
it is not configurable to match the generator and its energy source. In this paper a highly configurable self-priming
circuit is introduced and an analysis of the self-priming DEG cycle is performed to obtain design rules to optimize the
rate at which it can boost its operating voltage. In a case study we compare the performance of an initial prototype selfpriming
circuit with one that has been intentionally optimized. The optimized generator voltage climbed from 30 V up
to 1500 V in 27 cycles, whereas the same generator required 37 cycles when the suboptimal self-priming circuit was
Manipulators based on rigid, kinematically constrained structures and highly geared electromagnetic actuators are poorly
suited in applications where objects are soft, delicate, or have an irregular shape, especially if they operate outside of the
highly structured environment of a factory. Intrinsically soft DEA, imparted with the ability to self-sense enable the
creation of soft, smart artificial muscles provide a way forward. Inherent compliance simplifies manipulator trajectory
planning and force control, enables the manipulator to conform to the object, and provides natural damping of
mechanical disturbances. In this paper we present a simple proof-of-concept building block that could be used to create a
compliant DEA-based manipulator with self-sensing feedback. Capacitive self-sensing has been used to both detect
when contact is made with an object and gather information about the object's stiffness. Integrated into a manipulator,
this information could be used to adjust the grip directly, or used to reposition or reorient the manipulator to achieve a
Unlike electromagnetic actuators, Dielectric Elastomer Actuators (DEAs) can exert a static holding force without
consuming a significant amount of power. This is because DEAs are electrostatic actuators where the electric charges
exert a Maxwell stress. A charged DEA stores its electrical energy as potential energy, in a similar way to a capacitor. To
remove or reduce the Maxwell stress, the stored charge with its associated electrical energy must be removed. Current
DEA driver electronics simply dispose of this stored electrical energy. If this energy can be recovered, the efficiency of
DEAs would improve greatly. We present a simple and efficient way of re-using this stored energy by directly
transferring the energy stored in one DEA to another. An energy transfer efficiency of approximately 85% has been
Artificial muscles based on dielectric elastomers show enormous promise for a wide range of applications and are slowly
moving from the lab to industry. One problem for industrial uptake is the expensive, rigid, heavy and bulky high voltage
driver, sensor and control circuitry that artificial muscle devices currently require.
One recent development, the Dielectric Elastomer Switch(es) (DES), shows promise for substantially reducing auxiliary
circuitry and helping to mature the technology. DES are piezoresistive elements that can be used to form logic, driver,
and sensor circuitry. One particularly useful feature of DES is their ability to embed oscillatory behaviour directly into
an artificial muscle device.
In this paper we will focus on how DES oscillators can break down the barriers to industrial adoption for artificial
muscle devices. We have developed an improved artificial muscle ring oscillator and applied it to form a
mechanosensitive conveyor. The free running oscillator ran at 4.4 Hz for 1056 cycles before failing due to electrode
degradation. With better materials artificial muscle oscillators could open the door to robots with increased power to
weight ratios, simple-to-control peristaltic pumps, and commercially viable artificial muscle motors.
To reduce the likelihood of ventilator induced lung injury a neonatal lung simulator is developed based on Dielectric
Elastomer Actuators (DEAs). DEAs are particularly suited for this application due to their natural like response as well
as their self-sensing ability. By actively controlling the DEA, the pressure and volume inside the lung simulator can be
controlled giving rise to active compliance control. Additionally the capacitance of the DEA can be used as a
measurement of volume eliminating the integration errors that plague flow sensors.
Based on simulations conducted with the FEA package ABAQUS and experimental data, the characteristics of the lung
simulator were explored. A relationship between volume and capacitance was derived based on the self sensing of a
bubble actuator. This was then used to calculate the compliance of the experimental bubble actuator. The current results
are promising and show that mimicking a neonatal lung with DEAs may be possible.
Dielectric Elastomer Generator(s) (DEG) have many unique properties that give them advantages over
conventional electromagnetic generators. These include the ability to effectively generate power from slow and
irregular motions, low cost, relatively large energy density, and a soft and flexible nature. For DEG to generate
usable electrical energy circuits for charging (or priming) the stretched DEG and regulating the generated
energy when relaxed are required. Most prior art has focused on the priming challenge, and there is currently
very little work into developing circuits that address design issues for extracting the electrical energy and
converting it into a usable form such as low DC voltages (~10 V) for small batteries or AC mains voltage (~100
This paper provides a brief introduction to the problems of regulating the energy generated by DEG. A buck
converter and a charge pump are common DC-DC step-down circuits and are used as case studies to explore the
design issues inherent in converting the high voltage energy into a form suitable for charging a battery. Buck
converters are efficient and reliable but also heavy and bulky, making them suitable for large scale power
generation. The smaller and simpler charge pump, though a less effective energy harvester, is better for small
and discrete power generation. Future development in miniature DE fabrication is expected to reduce the high
operational voltages, simplifying the design of these circuits.
The Biomimetics Laboratory has developed a soft artificial muscle motor based on Dielectric Elastomers. The motor,
'Flexidrive', is light-weight and has low system complexity. It works by gripping and turning a shaft with a soft gear,
like we would with our fingers.
The motor's performance depends on many factors, such as actuation waveform, electrode patterning, geometries and
contact tribology between the shaft and gear. We have developed a finite element model (FEM) of the motor as a study
and design tool. Contact interaction was integrated with previous material and electromechanical coupling models in
ABAQUS. The model was experimentally validated through a shape and blocked force analysis.
Life shows us that the distribution of intelligence throughout flexible muscular networks is a highly successful solution
to a wide range of challenges, for example: human hearts, octopi, or even starfish. Recreating this success in engineered
systems requires soft actuator technologies with embedded sensing and intelligence. Dielectric Elastomer Actuator(s)
(DEA) are promising due to their large stresses and strains, as well as quiet flexible multimodal operation. Recently
dielectric elastomer devices were presented with built in sensor, driver, and logic capability enabled by a new concept
called the Dielectric Elastomer Switch(es) (DES). DES use electrode piezoresistivity to control the charge on DEA and
enable the distribution of intelligence throughout a DEA device.
In this paper we advance the capabilities of DES further to form volatile memory elements. A set reset flip-flop with
inverted reset line was developed based on DES and DEA. With a 3200V supply the flip-flop behaved appropriately and
demonstrated the creation of dielectric elastomer memory capable of changing state in response to 1 second long set and
reset pulses. This memory opens up applications such as oscillator, de-bounce, timing, and sequential logic circuits; all of
which could be distributed throughout biomimetic actuator arrays.
Future work will include miniaturisation to improve response speed, implementation into more complex circuits, and
investigation of longer lasting and more sensitive switching materials.
We use our thumbs and forefingers to rotate an object such as a control knob on a stereo system by
moving our finger relative to our thumb. Motion is imparted without sliding and in a precise manner. In
this paper we demonstrate how an artificial muscle membrane can be used to mimic this action. This is
achieved by embedding a soft gear within the membrane. Deformation of the membrane results in
deformation of the polymer gear and this can be used for motor actuation by rotating the shaft.
The soft motors were fabricated from 3M VHB4905 membranes 0.5mm thick that were pre-stretched
equibiaxially to a final thickness of 31 μm. Each membrane had polymer acrylic soft gears inserted at
the center. Sectors of each membrane (60° sector) were painted on both sides with conducting carbon
grease leaving gaps between adjoining sectors to avoid arcing between them. Each sector was
electrically connected to a power supply electrode on the rigid acrylic frame via narrow avenues of
carbon-grease. The motors were supported in rigid acrylic frames aligned concentrically. A flexible
shaft was inserted through both gears. Membranes were charged using a step wave PWM voltage
signal delivered using a Biomimetics Lab EAP Control unit. Both membrane viscoelasticity and the
resisting torque on the shaft influence motor speed by changing the effective circumference of the
This new soft motor opens the door to artificial muscle machines molded as a single part.
Sensing the electrical characteristics of a Dielectric Elastomer Actuator(s) (DEA) during actuation is critical to
improving their accuracy and reliability. We have created a self-sensing system for measuring the equivalent series
resistance of the electrodes, leakage current through the equivalent parallel resistance of the dielectric membrane, and the
capacitance of the DEA whilst it is being actuated. This system uses Pulse Width Modulation (PWM) to simultaneously
generate an actuation voltage and a periodic oscillation that enables the electrical characteristics of the DEA to be
sensed. This system has been specifically targeted towards low-power, portable devices. In this paper we experimentally
validate the self-sensing approach, and present a simple demonstration of closed loop control of the area of an expanding
dot DEA using capacitance feedback.
The global demand for renewable energy is growing, and ocean waves and wind are renewable energy
sources that can provide large amounts of power. A class of variable capacitor power generators called
Dielectric Elastomer Generators (DEG), show considerable promise for harvesting this energy because they
can be directly coupled to large broadband motions without gearing while maintaining a high energy density,
have few moving parts, and are highly flexible.
At the system level DEG cannot currently realize their full potential for flexibility, simplicity and low mass
because they require rigid and bulky external circuitry. This is because a typical generation cycle requires
high voltage charge to be supplied or drained from the DEG as it is mechanically deformed.
Recently we presented the double Integrated Self-Priming Circuit (ISPC) generator that minimized external
circuitry. This was done by using the inherent capacitance of DEG to store excess energy. The DEG were
electrically configured to form a pair of charge pumps. When the DEG were cyclically deformed, the charge
pumps produced energy and converted it to a higher charge form. In this paper we present the single ISPC
generator that contains just one charge pump. The ability of the new generator to increase its voltage through
the accumulation of generated energy did not compare favourably with that of the double ISPC generator.
However the single ISPC generator can operate in a wider range of operating conditions and the mass of its
external circuitry is 50% that of the double ISPC generator.
We are developing a hybrid Dielectric Elastomer Generator (DEG)-Microbial Fuel Cell (MFC) energy harvester . The
system is for EcoBot, an Autonomous Robot (AR) that currently uses its MFCs to extract electrical energy from
biomass, in the form of flies. MFCs, though reliable are slow to store charge. Thus, EcoBot operations are
characterized by active periods followed by dormant periods when energy stores recover. Providing an alternate
energy harvester such as a DEG, driven by wind or water, could therefore increase active time and also provide high
voltage energy for direct use by on-board systems employing dielectric elastomer actuators (DEAs).
Energy can be harvested from a DEG when work is done on its elastomer membrane.. However, the DEG requires an
initial charge and additional charge to compensate for losses due to leakage. The starting charge can be supplied by
the EcoBot MFC capacitor.
We have developed a self-primer circuit that uses some of the harvested charge to prime the membrane at each cycle.
The low voltage MFC initial priming charge was boosted using a voltage converter that was then electrically
disconnected. The DEG membrane was cyclically stretched producing charge that replenished leakage losses and
energy that could potentially be stored. A further study demonstrated that the DEG with self-primer circuit can boost
voltage from very low values without the need for a voltage converter, thus reducing circuit complexity and improving
Dielectric breakdown often leads to catastrophic failure in Dielectric Elastomer Actuator(s) (DEA). The resultant
damage to the dielectric membrane renders the DEA useless for future actuation, and in extreme cases the sudden
discharge of energy during breakdown can present a serious fire risk. The breakdown strength of DEA however is
heavily dependent on the presence of microscopic defects in the membrane giving its overall breakdown strength
inherent variability. The practical consequence is that DEA normally have to be operated far below their maximum
performance in order to achieve consistent reliability.
Predicting when DEA are about to suffer breakdown based on feedback will enable significant increase in effective DEA
performance without sacrificing reliability. It has been previously suggested that changes in the leakage current can be a
harbinger of dielectric breakdown; leakage current exhibits a sharp increase during breakdown. In this paper the
relationship between electric field and leakage current is investigated for simple VHB4905-based DEA. Particular
emphasis is placed on the behaviour of leakage current leading up to and during breakdown conditions. For a sample size
of nine expanding dot DEA, the DEA that failed at electric fields below the maximum tested exhibited noticeably higher
nominal power dissipation and a higher frequency of partial discharge events than the DEA that did not breakdown
during testing. This effect could easily be seen at electric fields well below that at which the worst performing DEA
Arrays of actuators are ubiquitous in nature for manipulation, pumping and propulsion. Often these arrays are
coordinated in a multi-level fashion with distributed sensing and feedback manipulated by higher level controllers. In
this paper we present a biologically inspired multi-level control strategy and apply it to control an array of Dielectric
Elastomer Actuators (DEA). A test array was designed consisting of three DEA arranged to tilt a set of rails on which a
ball rolls. At the local level the DEA were controlled using capacitive self-sensing state machines that switched the
actuator off and on when capacitive thresholds were exceeded, resulting in the steady rolling of the ball around the rails.
By varying the voltage of the actuators in the on state, it was possible to control the speed of the ball to match a set point.
A simple integral derivative controller was used to do this and an observer law was formulated to track the speed of the
The array demonstrated the ability to self start, roll the ball in either direction, and run at a range of speeds determined by
the maximum applied voltage. The integral derivative controller successfully tracked a square wave set point. Whilst the
test application could have been controlled with a classic centralised controller, the real benefit of the multi-level strategy
becomes apparent when applied to larger arrays and biomimetic applications that are ideal for DEA. Three such
applications are discussed; a robotic heart, a peristaltic pump and a ctenophore inspired propulsion array.
Dielectric Elastomer Generator(s) (DEG), are essentially variable capacitor power generators formed by hyper-elastic
dielectric materials sandwiched between flexible electrodes.
Electrical energy can be produced from a stretched, charged DEG by relaxing the mechanical deformation whilst
maintaining the amount of charge on its electrodes. This increases the distance between opposite charges and packs likecharges
more densely, increasing the amount of electrical energy. DEG show promise for harvesting energy from
environmental sources such as wind and ocean waves. DEG can undergo large inhomogeneous deformations and
electric fields during operation, meaning it can be difficult to experimentally determine optimal designs. Also, the circuit
that is used for harnessing DEG energy influences the DEG output by controlling the amount of charge on the DEG.
In this paper an integrated DEG model was developed where an ABAQUS finite element model is used to model the
DEG and data from this model is input to a system level LT-Spice circuit simulation. As a case-study, the model was
used as a design tool for analysing a diaphragm DEG connected to a self-priming circuit. That is, a circuit capable of
overcoming electrical losses by using some of the DEG energy to boost the charge in the system. Our ABAQUS model
was experimentally validated to predict the varying capacitance of a diaphragm DEG deformed inhomogeneously to
within 6% error.
Dielectric Elastomer (DE) transducers are essentially compliant capacitors fabricated from highly flexible materials that
can be used as sensors, actuators and generators. The energy density of DE is proportional to their dielectric constant
(εr), therefore an understanding of the dielectric constant and how it can be influenced by the stretch state of the material is required to predict or optimize DE device behavior. DE often operate in a stretched state. Wissler and Mazza, Kofod
et al., and Choi et al. all measured an εr of approximately 4.7 for virgin VHB, but their results for prestretched DE
showed that the dielectric constant decayed to varying degrees. Ma and Cross measured a dielectric constant of 6 for the
same material with no mention of prestretch. In an attempt to resolve this discrepancy, εr measurements were
performed on parallel plate capacitors consisting of virgin and stretched VHB4905 tape electroded with either gold
sputtered coatings or Nyogel 756G carbon grease. For an unstretched VHB tape, an εr of 4.5 was measured with both
electrode types, but the measured εr of equibiaxially stretched carbon specimens was lower by between 10 to 15%. The
dielectric constant of VHB under high fields was assessed using blocked force measurements from a dielectric elastomer
actuator. Dielectric constants ranging from 4.6-6 for stretched VHB were calculated using the blocked force tests.
Figure of merits for DE generators and actuators that incorporate their nonlinear behavior were used to assess the
sensitivity of these systems to the dielectric constant.
Human intention recognition is becoming a key part of powered prosthetics research. With the advent of smart
materials, the usefulness of powered prosthetics has increased. Correspondingly, there is a greater need for
control technology. Electromyography (EMG) has previously been used to control myoelectric hands; however
the approach to electrode placement has been speculative at best.
Carpi, Raspopovic and De Rossi have shown that dielectric elastomer actuators (DEAs) can be controlled by a
variety of human electrophysiological signals, including EMG. To control a DEA device with multiple degrees
of freedom using EMG, multiple electrode sites are required. This paper presents an approach to control an array
of DEAs using a series of electrodes and an optimized electrode data filtering scheme to maximize classification
accuracy when differentiating between hand grasps.
A silicon mould of a human forearm was created with an array of electrodes embedded within it. Data from each
electrode site was recorded using the Universal Electrophysiological Mapping (UnEmap) system developed at
the University of Auckland Bioengineering Institute for the amplification and filtering of multiple biopotential
The recorded data was then processed off-line, in order to calculate spatial gradients; this would determine
which electrode sites would give the best bipolar readings. The spatial gradients were then compared to each
other in order to find the optimal electrode sites. Several points in the extensor compartment of the forearm were
found to be useful in recognizing grasping, while several points in the flexor compartment of the forearm were
found to be useful in differentiating between grasps.
We describe a low profile and lightweight membrane rotary motor based on the dielectric elastomer actuator (DEA). In
this motor phased actuation of electroded sectors of the motor membrane imparts orbital motion to a central gear that
meshes with the rotor.
Two motors were fabricated: a three phase and four phase with three electroded sectors (120°/sector) and four sectors
(90°/sector) respectively. Square segments of 3M VHB4905 tape were stretched equibiaxially to 16 times their original
area and each was attached to a rigid circular frame. Electroded sectors were actuated with square wave voltages up to
2.5kV. Torque/power characteristics were measured. Contactless orbiter displacements, measured with the rotor
removed, were compared with simulation data calculated using a finite element model.
A measured specific power of approximately 8mW/g (based on the DEA membrane weight), on one motor compares
well with another motor technology. When the mass of the frame was included a peak specific power of 0.022mW/g was
calculated. We expect that motor performance can be substantially improved by using a multilayer DEA configuration,
enabling the delivery of direct drive high torques at low speeds for a range of applications.
The motor is inherently scalable, flexible, flat, silent in operation, amenable to deposition-based manufacturing
approaches, and uses relatively inexpensive materials.
Ctenophores or "comb jellies" are small sea creatures that propel themselves with rows of ciliated bending actuators or
'paddles'. In some species the actuators are coordinated via mechano-sensitivity; the physical contact of one paddle
triggers the motion of the next resulting in a wave of activation along the row. We seek to replicate this coordination
with an array of capacitive self-sensing Dielectric Elastomer Minimum Energy Structure(s) (DEMES) bending actuators.
For simplicity we focused on a conveyor application in air where four DEMES were used to roll cylindrical loads along
some rails. Such a system can automatically adjust to changing load dynamics and requires very little computational
overhead to achieve coordination.
We used a finite element modelling approach for DEMES development. The model used a hybrid Arruda-Boyce strain
energy function augmented with an electrostatic energy density term to describe the DEA behaviour. This allowed the
use of computationally efficient membrane elements giving simulation times of approximately 15 minutes and thus rapid
design development. Criteria addressing failure modes, the equilibrium state, and stroke of the actuators were developed.
The model had difficulty in capturing torsional instability in the frame thus design for this was conducted
The array was built and successfully propelled teflon and brass rollers up an incline. Noise in the capacitive sensor
limited the sensitivity of the actuators however with PCB circuit fabrication this problem should be solved.
We consider the embodiment of a microbial fuel cell using artificial muscle actuators. The microbial fuel cell digests
organic matter and generates electricity. This energy is stored in a capacitor bank until it is discharged to power one of
two complimentary artificial muscle technologies: the dielectric elastomer actuator and the ionic-polymer metal
composite. We study the ability of the fuel cell to generate useful actuation and consider appropriate configurations to
maximally exploit both of these artificial muscle technologies. A prototype artificial sphincter is implemented using a
dielectric elastomer actuator. Stirrer and cilia mechanisms motivate experimentation using ionic polymer metal
composite actuators. The ability of the fuel cell to drive both of these technologies opens up new possibilities for truly
biomimetic soft artificial robotic organisms.
The excellent overall performance and compliant nature of Dielectric Elastomer Actuators (DEAs) make them ideal
candidates for artificial muscles. Natural muscle however is much more than just an actuator, it provides position
feedback to the brain that is essential for the body to maintain balance and correct posture. If DEAs are to truly earn the
moniker of "artificial muscles" they need to be able to reproduce, if not improve on, this functionality.
Self-sensing DEAs are the ideal solution to this problem. This paper presents a system by which the capacitance of a
DEA can be sensed while it is being actuated and used for feedback control. This system has been strongly influenced by
the desire for portability i.e. designed for use in a battery operated microcontroller based system. It is capable of
controlling multiple independent DEAs using a single high voltage power supply. These features are important
developments for artificial muscle devices where accuracy and low mass are important e.g. a prosthetic hand or force-feedback
A numerical model of the electrical behaviour of the DEA that incorporates arbitrary leakage currents and the impact of
arbitrary variable capacitance has been created to model a DEA system. A robust capacitive self-sensing method that
uses a slew-rate controlled Pulse Width Modulation (PWM) signal and compensates for the effects of leakage current
and variable capacitance is presented. The numerical model is then used to compare the performance of this new method
with an earlier method previously published by the authors.
This paper presents an experimentally validated, nonlinear finite element model capable of predicting the blocked force
produced by Dielectric Elastomer Minimum Energy Structure (DEMES) bending actuators. DEMES consist of pre-stretched
dielectric elastomer (DE) films bonded to thin frames, the complex collapse of which can produce useful
bending actuation. Key advantages of DEMES include the ability to be fabricated in-plane, and the elimination of bulky
pre-stretch supports which are often found in other DE devices.
Triangular DEMES with 3 different pre-stretch ratios were fabricated. Six DEMES at each stretch ratio combination
were built to quantify experimental scatter which was significant due to the highly sensitive nature of the erect DEMES
equilibrium point. The best actuators produced approximately 10mN blocked force at 2500V.
We integrate an Arruda-Boyce model incorporating viscoelastic effects with the Proney series to describe the stress-strain
response of the elastomer, and a Neo-Hookean model to describe the frame. Maxwell pressure was simulated using
a constant thickness approximation and an isotropic membrane permittivity was calculated for the stress state of the
Experimental data was compared with the model and gave reasonable correlation. The model tended to underestimate the
blocked force due to a constant thickness assumption during the application of Maxwell stress. The spread due to
dielectric constant variance is also presented and compared with the spread of experimental scatter in the results.
Dielectric elastomer actuators (DEAs) are a promising artificial muscle technology that will enable new kinds of
prostheses and wearable rehabilitation devices. DEAs are driven by electric fields in the MV/m range and the dielectric
elastomer itself is typically 30μm in thickness or more. Large operating voltages, in the order of several kilovolts, are
then required to produce useful strains and these large voltages and the resulting electric fields could potentially pose
problems when DEAs are used in close proximity to the human body. The fringing electric fields of a DEA in close
association with the skin were modelled using finite element methods. The model was verified against a known analytic
solution describing the electric field surrounding a capacitor in air. The agreement between the two is good, as the
difference is less than 10% unless within 4.5mm of the DEA's lateral edges. As expected, it was found that for a DEA
constructed with thinner dielectric layers, the fringe field strength dropped in direct proportion to the reduction in applied
voltage, despite the internal field being maintained at the same level. More interestingly, modelling the electric field
around stacked DEAs showed that for an even number of layers the electric field is an order of magnitude less than for
an odd number of layers, due to the cancelling of opposing electric fields.
The future of Dielectric Elastomer Actuator (DEA) technology lies in miniaturizing individual elements and utilizing
them in array configurations, thereby increasing system fault tolerance and reducing operating voltages. An important
direction of DEA research therefore is real-time closed loop control of arrays of DEAs, particularly where multiple
degrees-of-freedom are desirable.
As the number of degrees-of-freedom increases a distributed control system offers a number of advantages with respect
to speed and efficiency. A low bandwidth digital control method for DEA devices is presented in this paper. Pulse Width
Modulation (PWM) is used as the basis for a current controlled DEA system that allows multiple degrees-of-freedom to
be controlled independently and in parallel using a single power supply set to a fixed voltage. The amplitude and the
duty cycle of the PWM signal control the current flow through a high speed, high voltage opto-coupler connected in
series with a DEA, enabling continuous control of both the output displacement and speed. Controlling the current in
real-time results in a system approaching a stable and robust constant charge system.
Closed loop control is achieved by measuring the rate of change of the voltage across the DEA in response to a step
change in the current input generated by the control signal. This enables the capacitance to be calculated, which in
combination with the voltage difference between the electrodes and the initial dimensions, enables the charge, strain state
and Maxwell pressure to be inferred. Future developments include integrating feedback information directly with the
control signal, leaving the controller to coordinate rather than control individual degrees-of-freedom.
Our work focuses on a contractile dielectric elastomer actuator (DEA) based on the McKibben pneumatic muscle
concept. A coupled-field ABAQUS (Hibbit, Karlsson & Sorensen, Inc., USA) FEA model has been developed where
the constraints of the orthotropic fibre weave and end caps of this actuator design are included. The implementation of
the Maxwell pressure model that couples electrical inputs to mechanical loads using the ABAQUS user subroutine
DLOAD is the focus of this paper. Our model was used to perform a study of actuator design parameters including the
fibre weave angle, dielectric thickness, and the DEA's length. At a fibre angle of 45° relative to the longitudinal axis, no
axial deformation was predicted by our model. A weave angle above this resulted in an axial expansion during
actuation, whereas axial compression occurred if the fibre angle was less than 45°. For instance, at a fibre angle of 30°
with respect to the longitudinal axis, this model predicted a compressive axial strain of 4.5% before mechanical failure
for an actuator with an outer radius of 2mm, wall thickness of 0.5mm, and length of 20mm.
This paper presents a method for creating a smart Dielectric Elastomer Actuator (DEA) with an integrated extension
sensor based on resistance and voltage measurement. Such a sensor can reduce cost, complexity, and weight compared to
external sensor solutions when used in applications where external sensing is difficult or costly, such as Micro-Electro-
Mechanical Systems (MEMS). The DEAs developed for integrated feedback are 20mm by 70mm and 30 &mgr;m thick
double layer silicone-dielectric actuators with reinforcing silicone ribs. Loose-carbon-powder electrodes produced the
best electrical and mechanical characteristics out of several possibilities tried.
Electrically isolated circuits were used to measure electrode resistance and driving voltage. These parameters were then
related to experiment using a model to predict DEA length. An offline regression method was used to fit the model to
within 2% of the full sensor range and the results were verified experimentally. The sensor feedback inaccuracy
immediately after a position step disturbance was shown to be around 20% of the full sensor range. This improved over 5
seconds to less than 5% as the transient creep effects in the silicone membrane that introduced the initial inaccuracy
decayed. Long term creep reduced the accuracy of the model, necessitating periodic retraining of the sensor. Overall the
sensor-estimated extension shows a very good qualitative or 'shape' match with the actual extension in the system.