Hydrogels have diverse chemical properties and can exhibit reversibly large mechanical deformations in response to external stimuli; these characteristics suggest that hydrogels are promising materials for soft robots. However, reported actuators based on hydrogels generally suffer from slow response speed and/or poor controllability due to intrinsic material limitations and electrode fabrication technologies. Here, we report a hydrogel actuator that operates at low voltages (<3 volts) with high performance (strain > 50%, energy density > 7 × 10 5 joules per cubic meter, and power density > 3 × 10 4 watts per cubic meter), surpassing existing hydrogel actuators and other types of electroactive soft actuators. The enhanced performance of our actuator is due to the formation of wrinkled nanomembrane electrodes that exhibit high conductivity and excellent mechanical deformation through capillary-assisted assembly of metal nanoparticles and deswelling-induced wrinkled structures. By applying an electric potential through the wrinkled nanomembrane electrodes that sandwich the hydrogel, we were able to trigger a reversible and substantial electroosmotic water flow inside a hydrogel film, which drove the controlled swelling of the hydrogel. The high energy efficiency and power density of our wrinkled nanomembrane electrode–induced actuator enabled the fabrication of an untethered insect-scale aquabot integrated with an on-board control unit demonstrating maneuverability with fast locomotion speed (1.02 body length per second), which occupies only 2% of the total mass of the robot.

The recent advances of wearable sensors are remarkable but there are still limitations that they need to be refabricated to tune the sensor for target signal. However, biological sensory systems have the inherent potential to adjust their sensitivity according to the external environment, allowing for a broad and enhanced detection. Here, we developed a Tunable, Ultrasensitive, Nature-inspired, Epidermal Sensor (TUNES) that the strain sensitivity was dramatically increased (GF ~30k) and the pressure sensitivity could be tuned (10–254 kPa−1) by preset membrane tension. The sensor adjusts the sensitivity to the pressure regime by preset tension, so it can measure a wide range (0.05 Pa–25 kPa) with the best performance: from very small signals such as minute pulse to relatively large signals such as muscle contraction and respiration. We verified its capabilities as a wearable health monitoring system by clinical trial comparing with pressure wire which is considered the current gold standard of blood pressure (r = 0.96) and home health care system by binary classification of Old’s/Young’s pulse waves via machine learning (accuracy 95%).

Anchoring components are added to wearable robots to ensure a stable interaction between the suits and the human body and to minimize the displacement of the suits. However, these components can apply pressure to the body and can cause user dissatisfaction, which can decrease willingness to use the suits. Therefore, this study aims to develop a suit-type soft-wearable robot platform for walking assistance by providing comfortable garment pressure to ensure user satisfaction. The first prototype of a wearable robot suit was developed with anchoring components on the shoulders, waist, and thighs based on previous research results. Wear tests were conducted to measure garment pressure depending on posture using pressure sensors, and satisfaction surveys were conducted. The second prototype design was then developed, and performance tests with flexible artificial muscles and a satisfaction survey were conducted. Regarding the first prototype, the participants felt more than normal pressure in the shoulders and relatively less pressure in the thighs and calves. Thus, compared to the first design, the second design ensured a decreased garment pressure and resulted in an improvement of overall user satisfaction. These results can help provide guidance in the development of wearable robots by taking pressure comfort and user satisfaction into consideration.

For legged robots, collecting tactile information is essential for stable posture and efficient gait. However, mounting sensors on small robots weighing less than 1 kg remain challenges in terms of the sensor’s durability, flexibility, sensitivity, and size. Crack-based sensors featuring ultra-sensitivity, small-size, and flexibility could be a promising candidate, but performance degradation due to crack growing by repeated use is a stumbling block. This paper presents an ultra-stable and tough bio-inspired crack-based sensor by controlling the crack depth using silver nanowire (Ag NW) mesh as a crack stop layer. The Ag NW mesh inspired by skin collagen structure effectively mitigated crack propagation. The sensor was very thin, lightweight, sensitive, and ultra-durable that maintains its sensitivity during 200,000 cycles of 0.5% strain. We demonstrate sensor’s feasibility by implementing the tactile sensation to bio-inspired robots, and propose statistical and deep learning-based analysis methods which successfully distinguished terrain type.