Soft sensors have been playing a crucial role in detecting different types of physical stimuli to part or the entire body of a robot, analogous to mechanoreceptors or proprioceptors in biology. Most of the currently available soft sensors with compact form factors can detect only a single deformation mode at a time due to the limitation in combining multiple sensing mechanisms in a limited space. However, realizing multiple modalities in a soft sensor without increasing its original form factor is beneficial, because even a single input stimulus to a robot may induce a combination of multiple modes of deformation. Here, we report a multifunctional soft sensor capable of decoupling combined deformation modes of stretching, bending, and compression, as well as detecting individual deformation modes, in a compact form factor. The key enabling design feature of the proposed sensor is a combination of heterogeneous sensing mechanisms: optical, microfluidic, and piezoresistive sensing. We characterize the performance on both detection and decoupling of deformation modes, by implementing both a simple algorithm of threshold evaluation and a machine learning technique based on an artificial neural network. The proposed soft sensor is able to estimate eight different deformation modes with accuracies higher than 95%. We lastly demonstrate the potential of the proposed sensor as a method of human-robot interfaces with several application examples highlighting its multifunctionality.

In this study, a liquid metal is directly printed on various types of surfaces using an automated dispensing system. A particular class of liquid metals called eutectic gallium–indium (Ga: 75.5% In: 24.5% by weight ratio) was chosen and printed on flat, inclined (20°, 30°, 40°, and 50°), and curved (   =  0.02, 0.03, 0.04, and 0.05 mm−1) surfaces. The inner diameter of the dispenser nozzle, the distance between the nozzle tip and the surface of the substrate, turned out to be the crucial parameters that determine the performance of printing, based on the experimental evaluation of the relationship between the trace width and the parameters. We were able to control the trace width under 200 m as small as 22 m by adjusting the parameters we tested. To the best of our knowledge, an EGaIn trace 22 m in width is the smallest one achieved by direct printing of a liquid metal on three-dimensional (3D) surfaces. Also, we were able to print not only straight lines but also curved patterns, such as spiral shapes. This will lead to the miniaturization of stretchable electronics with any pattern shapes consisting of straight lines and curves. As an example of applications of the proposed method, a micro-scale pressure sensor with a spiral trace pattern was fabricated, and its performance was evaluated with loading and unloading tests. Another application of the proposed method includes direct printing of stretchable electronics on surfaces with arbitrary shapes and curvatures. It was demonstrated with a seven-segment display circuit and soft sensors printed on a mannequin hand. We believe the proposed method and its applications will open a new space in development of soft electronics and robots.

Soft electromagnetic artificial muscles (SEAMs) that use electric currents are reported as their power sources. The proposed actuator consists of fully soft components: microfluidic coils, stretchable magnets, ferromagnetic silicone, and stretchable housings. The soft coils are fabricated by directly printing room‐temperature liquid metal on a stretchable substrate, enabling the generation of high‐density electromagnetic fields. Based on design optimization through modeling and simulation, the proposed actuators have a characteristic of bistability following the relationships of the forces acting on the components. Depending on the design configurations, the proposed actuators generate contraction and expansion motions as well as vibrations in a bidirectional manner, enabled by electromagnetic actuation. The main advantages of the proposed actuators are fully compliant structures, compact form factors, and short response times, which have not been observed in existing polymer‐based artificial muscles. Another advantage is the self‐detection of the actuation states by measuring the inductance change in the coils. Last, the modular design fully packaged with a coil and magnets in a soft housing makes it possible to easily resize and reconfigure the robotic systems with multiple actuator modules for different applications. Examples of applications demonstrated are a modular crawling robot, energy‐efficient grippers, a multi‐degrees of freedom (DOF) soft manipulator, and a high‐frequency swimming robot.

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