Make it stretch, make it glow: The skins of some cephalopods, such as the octopus, are highly flexible and contain color-changing cells. These cells are loaded with pigments that enable rapid and detailed camouflaging abilities. Larson et al. developed a stretchable electroluminescent actuator. The material could be highly stretched, could emit light, and could also sense internal and external pressure. A soft robot demonstrated these combined capabilities by stretching and emitting light as it moved. Science , this issue p. 1071

In the past few years, soft robotics has rapidly become an emerging research topic, opening new possibilities for addressing real‐world tasks. Perception can enable robots to effectively explore the unknown world, and interact safely with humans and the environment. Among all extero‐ and proprioception modalities, the detection of mechanical cues is vital, as with living beings. A variety of soft sensing technologies are available today, but there is still a gap to effectively utilize them in soft robots for practical applications. Here, the developments in soft robots with mechanical sensing are summarized to provide a comprehensive understanding of the state of the art in this field. Promising sensing technologies for mechanically perceptive soft robots are described, categorized, and their pros and cons are discussed. Strategies for designing soft sensors and criteria to evaluate their performance are outlined from the perspective of soft robotic applications. Challenges and trends in developing multimodal sensors, stretchable conductive materials and electronic interfaces, modeling techniques, and data interpretation for soft robotic sensing are highlighted. The knowledge gap and promising solutions toward perceptive soft robots are discussed and analyzed to provide a perspective in this field.

A soft tactile sensor able to detect both normal and tangential forces is fabricated with a simple method using conductive textile. Owing to the multi-layered architecture, the capacitive-based tactile sensor is highly sensitive (less than 10 mg and 8 μm, for minimal detectable weight and displacement, respectively) within a wide normal force range (potentially up to 27 N (400 kPa)) and natural touch-like tangential force ranges (from about 0.5 N to 1.8 N). Being flexible, soft, and low cost, this sensor represents an original approach in the emulation of natural touch.

Revealing human movement requires lightweight, flexible systems capable of detecting mechanical parameters (like strain and pressure) while being worn comfortably by the user, and not interfering with his/her activity. In this work we address such multifaceted challenge with the development of smart garments for lower limb motion detection, like a textile kneepad and anklet in which soft sensors and readout electronics are embedded for retrieving movement of the specific joint. Stretchable capacitive sensors with a three-electrode configuration are built combining conductive textiles and elastomeric layers, and distributed around knee and ankle. Results show an excellent behavior in the ~30% strain range, hence the correlation between sensors’ responses and the optically tracked Euler angles is allowed for basic lower limb movements. Bending during knee flexion/extension is detected, and it is discriminated from any external contact by implementing in real time a low computational algorithm. The smart anklet is designed to address joint motion detection in and off the sagittal plane. Ankle dorsi/plantar flexion, adduction/abduction, and rotation are retrieved. Both knee and ankle smart garments show a high accuracy in movement detection, with a RMSE less than 4° in the worst case.

We present the design and development of a plant-inspired robot, named Plantoid, with sensorized robotic roots. Natural roots have a multi-sensing capability and show a soft bending behaviour to follow or escape from various environmental parameters (i.e., tropisms). Analogously, we implement soft bending capabilities in our robotic roots by designing and integrating soft spring-based actuation (SSBA) systems using helical springs to transmit the motor power in a compliant manner. Each robotic tip integrates four different sensors, including customised flexible touch and innovative humidity sensors together with commercial gravity and temperature sensors. We show how the embedded sensing capabilities together with a root-inspired control algorithm lead to the implementation of tropic behaviours. Future applications for such plant-inspired technologies include soil monitoring and exploration, useful for agriculture and environmental fields.

Sensors detecting angles created by deformable structures play an increasing role in soft robotics and wearable systems. However, the typical sensing method based on strain measurement strongly depends on the viscoelastic behaviors of soft substrates and on the location of sensors that affect the sensing reliability. In this work, the changes in magnetic field coupling produced in space by planar coil deformation are investigated, for implementing a new direct transduction strategy, the soft inductive angle sensing (SIAS). A numerical analysis tool is developed for rigorously studying the inductance variations resulting from planar coils’ bending, folding, and folding with a small arc. Copper or liquid metal coils, having different shapes, pitches, and sizes are built and characterized. Results show that the SIAS is hysteresis‐free, velocity‐independent, highly sensitive, ultrastable, and with fast response, guaranteeing highly precise (0.1° incremental folding angle change) and reliable measurements. It is insensitive to coil materials and to behavior of embedding soft materials, and scalable (across 10 times scale). The SIAS is adopted in three case studies (a self‐sensing origami, a sensorized soft pneumatic actuator, and a wearable sensor) to highlight its low implementation complexity, high‐performance, and versatility, providing some insights on the enormous potential of this mechanism.