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.

An innovative processing strategy for fabricating soft structures that possess electric- and humidity-driven active/passive actuation capabilities along with touch- and humidity-sensing properties is reported. The intrinsically multifunctional material comprises an active thin layer of poly(3,4-ethylenedioxythiophene):poly­(styrene sulfonate) in a double-layered structure with a silicone elastomer and provides an opportunity toward developing a new class of smart structures for soft robotics.

Octopuses have impressive manipulation capabilities empowered by the intrinsic adaptation of their soft arms combined with distributed suckers. Drawing inspiration from the arm morphology and abilities of the octopus, the integrated design of a conical soft robotic arm endowed with suction cups is presented herein. The proposed arm exploits soft robotic technologies as in materials (combining stiff and soft silicones) and actuation (tendons to drive motion and fluidic channels for suction cup actuation) for retrieving objects in confined spaces of unknown shapes and sizes. The soft arm is able to grasp varied and complex‐shaped objects, to move in air, water, and oil, and to retrieve items immersed in a 70 mm diameter pipe, under pressure (up to 18 bar). Suction cups enable the arm to retrieve objects that would be impossible to grasp without them and help in improving the grasping force up to ≈1.4 times in air, ≈2.4 times in water, and ≈12.5 times in oil. The enhanced holding force (up to 3.3 N, ≈3.9 times arm weight) and a wide spectrum of objects negotiable by the arm make it a universal tool for object retrieval in confined spaces and wet conditions.

Self-growing robots are an emerging solution in soft robotics for navigating, exploring, and colonizing unstructured environments. However, their ability to grow and move in heterogeneous three-dimensional (3D) spaces, comparable with real-world conditions, is still developing. We present an autonomous growing robot that draws inspiration from the behavioral adaptive strategies of climbing plants to navigate unstructured environments. The robot mimics climbing plants’ apical shoot to sense and coordinate additive adaptive growth via an embedded additive manufacturing mechanism and a sensorized tip. Growth orientation, comparable with tropisms in real plants, is dictated by external stimuli, including gravity, light, and shade. These are incorporated within a vector field method to implement the preferred adaptive behavior for a given environment and task, such as growth toward light and/or against gravity. We demonstrate the robot’s ability to navigate through growth in relation to voids, potential supports, and thoroughfares in otherwise complex habitats. Adaptive twining around vertical supports can provide an escape from mechanical stress due to self-support, reduce energy expenditure for construction costs, and develop an anchorage point to support further growth and crossing gaps. The robot adapts its material printing parameters to develop a light body and fast growth to twine on supports or a tougher body to enable self-support and cross gaps. These features, typical of climbing plants, highlight a potential for adaptive robots and their on-demand manufacturing. They are especially promising for applications in exploring, monitoring, and interacting with unstructured environments or in the autonomous construction of complex infrastructures.