A new method, embedded-3D printing (e-3DP), is reported for fabricating strain sensors within highly conformal and extensible elastomeric matrices. e-3DP allows soft sensors to be created in nearly arbitrary planar and 3D motifs in a highly programmable and seamless manner. Several embodiments are demonstrated and sensor performance is characterized.

A new method for fabricating textile integrable capacitive soft strain sensors is reported, based on multicore-shell fiber printing. The fiber sensors consist of four concentric, alternating layers of conductor and dielectric, respectively. These wearable sensors provide accurate and hysteresis-free strain measurements under both static and dynamic conditions.

Wearable robots based on soft materials will augment mobility and performance of the host without restricting natural kinematics. Such wearable robots will need soft sensors to monitor the movement of the wearer and robot outside the lab. Until now wearable soft sensors have not demonstrated significant mechanical robustness nor been systematically characterized for human motion studies of walking and running. Here, we present the design and systematic characterization of a soft sensing suit for monitoring hip, knee, and ankle sagittal plane joint angles. We used hyper-elastic strain sensors based on microchannels of liquid metal embedded within elastomer, but refined their design with the use of discretized stiffness gradients to improve mechanical durability. We found that these robust sensors could stretch up to 396% of their original lengths, would restrict the wearer by less than 0.17% of any given joint’s torque, had gauge factor sensitivities of greater than 2.2, and exhibited less than 2% change in electromechanical specifications through 1500 cycles of loading–unloading. We also evaluated the accuracy and variability of the soft sensing suit by comparing it with joint angle data obtained through optical motion capture. The sensing suit had root mean square (RMS) errors of less than 5° for a walking speed of 0.89 m/s and reached a maximum RMS error of 15° for a running speed of 2.7 m/s. Despite the deviation of absolute measure, the relative repeatability of the sensing suit’s joint angle measurements were statistically equivalent to that of optical motion capture at all speeds. We anticipate that wearable soft sensing will also have applications beyond wearable robotics, such as in medical diagnostics and in human–computer interaction.

Many pneumatic energy sources are available for use in autonomous and wearable soft robotics, but it is often not obvious which options are most desirable or even how to compare them. To address this, we compare pneumatic energy sources and review their relative merits. We evaluate commercially available battery-based microcompressors (singly, in parallel, and in series) and cylinders of high-pressure fluid (air and carbon dioxide). We identify energy density (joules/gram) and flow capacity (liters/gram) normalized by the mass of the entire fuel system (versus net fuel mass) as key metrics for soft robotic power systems. We also review research projects using combustion (methane and butane) and monopropellant decomposition (hydrogen peroxide), citing theoretical and experimental values. Comparison factors including heat, effective energy density, and working pressure/flow rate are covered. We conclude by comparing the key metrics behind each technology. Battery-powered microcompressors provide relatively high capacity, but maximum pressure and flow rates are low. Cylinders of compressed fluid provide high pressures and flow rates, but their limited capacity leads to short operating times. While methane and butane possess the highest net fuel energy densities, they typically react at speeds and pressures too high for many soft robots and require extensive system-level development. Hydrogen peroxide decomposition requires not only few additional parts (no pump or ignition system) but also considerable system-level development. We anticipate that this study will provide a framework for configuring fuel systems in soft robotics.

One of the challenges to rapidly manufacturing flexible electronics is the complexity involved in printing circuitry from stretchable conductors. Eutectic gallium alloys are typically used as the conductive material because they have unique high conductivity, self‐healing, and stretchable properties. However, limited 3D printing has been demonstrated by leveraging the structural stabilization provided by the thin gallium oxide film. Vertical structures are difficult to print with a liquid metal (LM) due to the low viscosity and high surface tension of the gallium alloy, which easily leads to coalescence. A method is presented to alter the physical structure of the liquid metal through the incorporation of a conductive nano‐ or micronickel fillers. The resulting rheological modification of the liquid metal to a paste drastically increases the fluidic elastic modulus and yield stress, rendering it 3D printable. Further, the modification retains the high electrical conductivity (3.9 × 106 ± 9.5 × 105 S m−1) and stretchability (over 350% strain) of pure liquid metal. The ability to print 3D standing structures using this highly conductive metal paste opens up new opportunities to manufacture more complex stretchable electronics.