Cephalopods such as octopuses have a combination of a stretchable skin and color-tuning organs to control both posture and color for visual communication and disguise. We present an electroluminescent material that is capable of large uniaxial stretching and surface area changes while actively emitting light. Layers of transparent hydrogel electrodes sandwich a ZnS phosphor-doped dielectric elastomer layer, creating thin rubber sheets that change illuminance and capacitance under deformation. Arrays of individually controllable pixels in thin rubber sheets were fabricated using replica molding and were subjected to stretching, folding, and rolling to demonstrate their use as stretchable displays. These sheets were then integrated into the skin of a soft robot, providing it with dynamic coloration and sensory feedback from external and internal stimuli.

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.