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Abstract Snails can stably slide across a surface with only a single high-payload sucker, offering an efficient adhesive locomotion mechanism for next-generation climbing robots. The critical factor for snails’ sliding suction behaviour is mucus secretion, which reduces friction and enhances suction. Inspired by this, we proposed an artificial sliding suction mechanism. The sliding suction utilizes water as an artificial mucus, which is widely available and evaporates with no residue. The sliding suction allows a lightweight robot (96 g) to slide vertically and upside down, achieving high speeds (rotation of 53°/s and translation of 19 mm/s) and high payload (1 kg as tested and 5.03 kg in theory), and does not require energy during adhesion. Here, we show that the sliding suction is a low-cost, energy-efficient, high-payload and clean adhesive locomotion strategy, which has high potential for use in climbing robots, outdoor inspection robots and robotic transportation.

Abstract Edible electronics leverages the electronic properties of food‐derived materials to deliver safer technologies that can be degraded (or digested) in the environment (or body) at the end‐of‐life. Sensors will be central to future smart edible robots, and edible strain sensors are particularly interesting as they can transduce deformation, providing real time feedback of the movement. Yet, to date edible strain sensors have been limited to the use of ionic conductive hydrogels, resulting in sensors not directly suitable for direct current operation and therefore not compatible with existing edible batteries. Here, the first edible strain sensor based on electronic conduction made of a novel conductive ink sprayed over an edible substrate is presented. The ink formulation consists of activated carbon (conductor), Haribo gummy bears (binder), and water−ethanol mixture (dispersant). The ink, deposited on multiple substrates by spray deposition, produces edible electrically conductive composite coatings with resistivity of ≈50 Ω cm. The coatings were used as a piezoresistive layer to fabricate strain sensors with gauge factors of 19−92 suitable for direct current operation. As a proof‐of‐concept of future edible systems, the sensor is validated by integrating it within a gelatin actuator to produce a sensorized gripper powered by an edible battery.

Multimodal perception is the predominant means by which individuals experience and interact with the world. However, sensory dysfunction or loss can significantly impede this process. In such cases, cross-modality research offers valuable insight into how we can compensate for these sensory deficits through sensory substitution. Although sight and hearing are both used to estimate the distance to an object (e.g., by visual size and sound volume) and the perception of distance is an important element in navigation and guidance, it is not widely studied in cross-modal research. We investigate the relationship between audio and vibrotactile frequencies (in the ranges 47-2,764 Hz and 10-99 Hz, respectively) and distances uniformly distributed in the range 1-12 m. In our experiments participants mapped the distance (represented by an image of a model at that distance) to a frequency via adjusting a virtual tuning knob. The results revealed that the majority (more than 76%) of participants demonstrated a strong negative monotonic relationship between frequency and distance, across both vibrotactile (represented by a natural log function) and auditory domains (represented by an exponential function). However, a subgroup of participants showed the opposite positive linear relationship between frequency and distance. The strong cross-modal sensory correlation could contribute to the development of assistive robotic technologies and devices to augment human perception. This work provides the fundamental foundation for future assisted HRI applications where a mapping between distance and frequency is needed, for example for people with vision or hearing loss, drivers with loss of focus or response delay, doctors undertaking teleoperation surgery, and users in augmented reality (AR) or virtual reality (VR) environments.

The increasing impact of technology disposal and e-waste on the environment has driven robotics scientists to develop more sustainable robots. Biodegradable and edible shape-memory polymer artificial muscles represent an important robotic component that enables environmentally modulated deformation and movement. The need for finer behavioral control of artificial muscles also requires proprioceptive functionality. Here we report the first edible shape-memory oleogel composites that monolithically couple shape-memory actuation and color-change sensing within one material. The shape recovery and color change capabilities were characterized and two sustainable soft robots, a robotic gripper and a biomimetic flower, were constructed to demonstrate their potential for the development of sustainable and edible robotics.

Abstract Background Soft, wearable, powered exoskeletons are novel devices that may assist rehabilitation, allowing users to walk further or carry out activities of daily living. However, soft robotic exoskeletons, and the more commonly used rigid exoskeletons, are not widely adopted clinically. The available evidence highlights a disconnect between the needs of exoskeleton users and the engineers designing devices. This review aimed to explore the literature on physiotherapist and patient perspectives of the longer-standing, and therefore greater evidenced, rigid exoskeleton limitations. It then offered potential solutions to these limitations, including soft robotics, from an engineering standpoint. Methods A state-of-the-art review was carried out which included both qualitative and quantitative research papers regarding patient and/or physiotherapist perspectives of rigid exoskeletons. Papers were themed and themes formed the review’s framework. Results Six main themes regarding the limitations of soft exoskeletons were important to physiotherapists and patients: safety; a one-size-fits approach; ease of device use; weight and placement of device; cost of device; and, specific to patients only, appearance of the device. Potential soft-robotics solutions to address these limitations were offered, including compliant actuators, sensors, suit attachments fitting to user’s body, and the use of control algorithms. Conclusions It is evident that current exoskeletons are not meeting the needs of their users. Solutions to the limitations offered may inform device development. However, the solutions are not infallible and thus further research and development is required.

This data article presents four experimental sets of results related to flax fibre composites with epoxy shape memory polymer matrix: water vapor absorption, mass diffusion immersed in water, hygroscopic expansion, mechanical properties. The water vapor absorption tests are described in raw data related to four types of laminates with weights measured at different relative humidity (0%, 9%, 33%, 44%,75%, 85% and 100%). The mass diffusion experiments are related to weights of immersed samples over time. The unidirectional composite hygroscopic expansion is also measured along the fibre longitude and transverse directions. The mechanical properties of flax composite at various temperatures (20°C, 40°C, 60°C, 80°C and 100°C) and humidity environments (50% and immersed) are also described. Load-displacement diagrams of the hygromorph composites are converted into stress-strain diagrams via a compliance calibration, from which the tensile moduli are extracted. The data presented in this article can provide a benchmark for the development of new models, or for the determination of other properties via post processing. The detailed interpretation of the data can be found in [1]. The data is available in the Mendeley Data repository at [2].

Robots operating in changing underwater environments may be required to adapt to these varying conditions. In tidal estuaries, for example, where the degree of salinity cycles in step with the level of the water, a robot may need to adapt its behaviour depending on the position of the tide. In freshwater bodies, the unexpected presence of a pollutant may also require the robot to respond by altering its behaviour. Embodying this sensing and response in the body of the robot means that adaptivity to the environment can be achieved without resorting to centralised control. This can also allow direct responsivity using ‘free’ environmental energy, actuating without requiring stored onboard energy. In this work we present a soft artificial muscle, the contraction of which varies in response to the salinity the water surrounding it. The novel actuator uses a super-absorbent polymer gel encapsulated within a series of discrete cells. This gel readily absorbs water through the membrane wall of the actuator, and can swell to over 300 times its initial volume. This swelling generates significant pressure, changing the shape of the cells and driving the contraction of the muscle. The degree of swelling is significantly reduced by the presence of salts and pollutants in the surrounding water, so transitioning from a freshwater to a saltwater environment causes the muscle to relax. In this paper, we discuss the design and fabrication of these superabsorbent polymer-based Bubble Artificial Muscle (SAP-BAM) actuators. The tensile properties of the muscle under actuated (fresh water) and relaxed (salt water) conditions are characterised, showing a maximum generated force of 10.96N. The length response under constant load for a full actuation cycle is given, showing a maximum contraction of 27.5% of the initial length at 1N load, and the performance over repeated actuation and relaxation cycles is shown. The SAP-BAM muscles are straightforward to fabricate and are composed of low-cost, freely-available materials. Many existing pneumatically-actuated muscles can be modified to use the approach taken for this muscle. The muscle presented in this work represents the first example of a new class of super-absorbent polymer-driven environmental soft artificial muscles.

The development of biodegradable soft robotics requires an appropriate eco-friendly source of energy. The use of Microbial Fuel Cells (MFCs) is suggested as they can be designed completely from soft materials with little or no negative effects to the environment. Nonetheless, their responsiveness and functionality is not strictly defined as in other conventional technologies, i.e. lithium batteries. Consequently, the use of artificial intelligence methods in their control techniques is highly recommended. The use of neural networks, namely a nonlinear autoregressive network with exogenous inputs was employed to predict the electrical output of an MFC, given its previous outputs and feeding volumes. Thus, predicting MFC outputs as a time series, enables accurate determination of feeding intervals and quantities required for sustenance that can be incorporated in the behavioural repertoire of a soft robot.

Electro-ribbon actuators are lightweight, flexible, high-performance actuators for next generation soft robotics. When electrically charged, electrostatic forces cause the electrode ribbons to progressively zip together through a process called dielectrophoretic liquid zipping (DLZ), delivering contractions of more than 99% of their length. Electro-ribbon actuators exhibit pull-in instability, and this phenomenon makes them challenging to control: below the pull-in voltage threshold, actuator contraction is small, while above this threshold, increasing electrostatic forces cause the actuator to completely contract, providing a narrow contraction range for feedforward control. We show that application of a time-varying voltage profile that starts above pull-in threshold, but subsequently reduces, allows access to intermediate steady-states not accessible using traditional feed-forward control. A modified proportional-integral closed-loop controller is proposed (Boost-PI), which incorporates a variable boost voltage to temporarily elevate actuation close to, but not exceeding, the pull-in voltage threshold. This primes the actuator for zipping and drastically reduces rise time compared with a traditional PI controller. A multi-objective parameter-space approach was implemented to choose appropriate controller gains by assessing the metrics of rise time, overshoot, steady-state error, and settle time. This proposed control method addresses a key limitation of the electro-ribbon actuators, allowing the actuator to perform staircase and oscillatory control tasks. This significantly increases the range of applications which can exploit this new DLZ actuation technology.

It is desirable to equip soft-smart materials and structures with actuation, sensing, and adhesion functionalities. A multifunctional stretchable bifilar coil capable of soft adhesion and sensing is presented in this work. The fully-soft flat bifilar coil, based on the Tesla coil design, can be fabricated by encapsulating a cost-effective, easy-to-implement, and scalable liquid-metal-elastomer-tube in a soft planar composite. By combining pneumatic actuation of the soft coil with application of a high voltage across the two electrodes, a morphologically adaptive and soft electroadhesive is demonstrated and can be used to lift lightweight and flexible textiles from curved surfaces. At the same time, capacitive, resistive, and inductive sensing functionalities can be achieved by interrogating the bifilar coil. This stretchable bifilar coil has the potential to enable soft multimodal adhesives such as entirely-soft electro-magneto adhesives with incorporated soft resistive, capacitive, and inductive sensing for soft robotics and implantable devices. Keywords: Stretchable bifilar coil, Liquid metal elastomer composite, Multimodal soft sensing, Soft adhesion

Soft robots have the potential to diminish the need for humans to venture into unsuitable environments or work in extreme conditions. While their soft nature gives them the advantage of being adaptable to changing environments, their control can be challenging because of the compliance that makes them effective. In this paper we present RUBIC: the Rolling, Untethered, Ballooning, Intelligent Cube, that overcomes some of the difficulties of 2D control by constraining motion to a discretised Cartesian space. RUBIC's method of locomotion is by rolling from one face of the cube to another, in any one of four directions. This motion causes it to move within a 2D grid structure, the dimensions of which are defined by the cube's characteristic length. When in its resting position RUBIC is inherently stable and forms a safe platform for tasks including taking measurements and soil samples, for localization and ad hoc network infrastructure, and as the foundation for larger robots and structures. We present the design of RUBIC's body, the four pneumatic ballooning actuators per face that generate its unique gait, and the control systems for locomotion and obstacle climbing. We consider constraints imposed by the design and fabrication methods including physical dimension and weight, material properties and control fidelity. An alternative locomotion scheme is proposed to improve the speed and linearity which also increases the distance traveled per roll. RUBIC travels with a mean locomotion accuracy of 4.58° deviation and successfully traverses steps up to 35% of its own height. The discretisation of a soft robotics workspace, as demonstrated by RUBIC, has advantages for safe and predictable locomotion and has applications in both structured and hazardous environments.

We present and evaluate the concept of FeelMusic and evaluate an implementation of it. It is an augmentation of music through the haptic translation of core musical elements. Music and touch are intrinsic modes of affective communication that are physically sensed. By projecting musical features such as rhythm and melody into the haptic domain, we can explore and enrich this embodied sensation; hence, we investigated audio-tactile mappings that successfully render emotive qualities. We began by investigating the affective qualities of vibrotactile stimuli through a psychophysical study with 20 participants using the circumplex model of affect. We found positive correlations between vibration frequency and arousal across participants, but correlations with valence were specific to the individual. We then developed novel FeelMusic mappings by translating key features of music samples and implementing them with “Pump-and-Vibe”, a wearable interface utilising fluidic actuation and vibration to generate dynamic haptic sensations. We conducted a preliminary investigation to evaluate the FeelMusic mappings by gathering 20 participants’ responses to the musical, tactile and combined stimuli, using valence ratings and descriptive words from Hevner’s adjective circle to measure affect. These mappings, and new tactile compositions, validated that FeelMusic interfaces have the potential to enrich musical experiences and be a means of affective communication in their own right. FeelMusic is a tangible realisation of the expression “feel the music”, enriching our musical experiences.

Magnetic resonance imaging (MRI) is a crucial tool for clinical brain tumor detection and delineation. Since the process of gross tumor volume delineation resides with clinicians, a better understanding of how they perform this task is required if improvements in life expectancy are to be made. Novice-expert comparison studies have been used to examine the effect of expertise on abnormality detection, but little research has investigated expertise-related differences in brain tumor delineation. In this study, undergraduate students (novices) and radiologists (experts) inspected a combination of T1 and T2 single and whole brain MRI scans, each containing a tumor. Using a tablet and stylus to provide an interactive environment, participants had an unlimited amount of time to scroll freely through the MRI slices and were instructed to delineate (i.e., draw a boundary) around any tumorous tissue. There was no reliable evidence for a difference in the gross tumor volume or total number of slices delineated between experts and novices. Agreement was low across both expertise groups and significantly lower at peripheral locations within a tumor than central locations. There was an interaction between expertise level and location within a tumor with experts displaying higher agreement at the peripheral slices than novices. An effect of brain image set on the order in which participants inspected the slices was also observed. The implications of these results for the training undertaken by early career radiologists and current practices in hospitals are discussed.

Effective tactile sensing for artificial platforms remains an open issue in robotics. This study investigates the performance of a soft biologically-inspired artificial fingertip in active exploration tasks. The fingertip sensor replicates the mechanisms within human skin and offers a robust solution that can be used both for tactile sensing and gripping/manipulating objects. The softness of the optical sensor’s contact surface also allows safer interactions with objects. High-level tactile features such as edges are extrapolated from the sensor’s output and the information is used to generate a tactile image. The work presented in this paper aims to investigate and evaluate this artificial fingertip for 2D shape reconstruction. The sensor was mounted on a robot arm to allow autonomous exploration of different objects. The sensor and a number of human participants were then tested for their abilities to track the raised perimeters of different planar objects and compared. By observing the technique and accuracy of the human subjects, simple but effective parameters were determined in order to evaluate the artificial system’s performance. The results prove the capability of the sensor in such active exploration tasks, with a comparable performance to the human subjects despite it using tactile data alone whereas the human participants were also able to use proprioceptive cues.

Electroadhesion is a promising adhesion mechanism for robotics and material handling applications with advantages over existing technologies including enhanced adaptability, gentle/flexible handling, reduced complexity, and ultra-low energy consumption. Current electroadhesive (EA) grippers, however, require extra components and their associated electronics to make them sensorially capable. In addition, current planar EA grippers have difficulty adhering to non-planar surfaces and picking up non-flat objects. We present a monolithic, shape-adaptive, and self-sensing EA composite with integral dielectric elastomer actuation (DEA). This new EA-DEA composite gripper is not only proprioceptive (it can sense internal deformations) and exteroceptive (it can sense and differentiate between surfaces that it touches) but can also actively morph and adapt to curved surfaces. By integrating a high voltage self-sensing unit with the EA-DEA composite, coupled gripping and sensing capabilities can be achieved. This is because combined actions of membrane deformations by the Maxwell force and surface attraction by the EA force can be obtained by using only one voltage source due to the employment of a dual-mode parallel-and-coplanar electrode pattern. The proposed approach has the potential to significantly improve the intelligence of EA gripping technologies and increase their use in intelligent material sorting, grasping, and manipulation applications. Keywords: Dielectric elastomer, Electroadhesion, Proprioception, Exteroception, Soft electroadhesive, Active shape morphing

Smart textiles are flexible materials with interactive capabilities such as sensing, actuation, and computing, and in recent years have garnered considerable interest. Shape-memory alloy (SMA) wire is a well-suited for smart textiles due to its high strength, small size, and low mass. However, the contraction of SMA wire is low, limiting its usefulness. One solution to increasing net contraction is to use a long SMA wire and guide it inside a tube that is wound back and forth or coiled inside a smart textile. In this article, we characterize the performance of tube-guided SMA wire actuators. We investigate the effect of turn radius and number of loops, showing that the stroke of an SMA-based system can be improved by up to 69.81% using the tube-guided SMA wire actuator concept. Finally, we investigate how tube-guided SMA wire actuators can be lubricated to improve their performance. Coarse graphite powder and tungsten disulfide lubricant both delivered improvements in stroke compared with an unlubricated system.

Smart fabrics offer the potential for a new generation of soft robotics and wearable technologies through the fusion of smart materials, textiles and electrical circuitries. Conductive and stretchable textiles have inherent compliance and low resistance that are suitable for driving artificial muscle actuators and are potentially safer electrode materials for soft actuation technologies. We demonstrate how soft electroactive actuating structures can be designed and fabricated from conducting textiles. We first quantitatively analyse a range of stretchable conductive textiles for dielectric elastomer actuators (DEAs). We found that conductive-knit textiles are more suitable for unidirectional DEA applications due to the largest difference (150%) in principle strain axes, whereas isotropic textiles are more suited to bidirectional DEA applications due to the smallest (11.1%) principle strain difference. Finally, we demonstrate controllable breathability through a planar e-textile DEA-driven skin and show thermal regulation in a wearable prototype that exploits soft actuation and kirigami.

Bouncing locomotion is used frequently in the animal kingdom for high speed movement over land. Animals also change their stiffness and shape to improve their locomotion ability. Both bouncing movement and stiffness- and shape-changing capabilities have been recently explored in robotics. In this paper a novel soft locomotion robot, VibroBot, is presented, capable of moving using a bouncing gait by inducing whole-body oscillations through rotation of an internal out-of-balance mass. VibroBot is capable of changing both its stiffness and shape to tackle challenging terrain and to overcome obstacles. When the robot is stiff, it is capable of high-frequency oscillatory locomotion suited to movement on hard surfaces, while in a compliant state it uses a lower-frequency higher-amplitude hopping gait suitable for travelling over soft or loose ground. Forward speeds of 8.5 cm/s (0.34 body lengths per second) on hard floor in VibroBot’s stiff state and 5 cm/s (0.2 body lengths per second) on sand in its compliant state were recorded. VibroBot can also selectively change its shape to climb obstacles with heights up to 3 cm (20% of the robot’s height in its stiff state), far greater than its hopping apex height (1 cm). Both simple bouncing gaits and stiffness- and shape-changing abilities show great promise for improving the locomotion abilities of soft robots.