Vibrissae are an important tactile sense organ of many mammals, in particular rodents like rats and mice. For instance, these animals use them in order to detect different object features, e.g., object-distances and -shapes. In engineering, vibrissae have long been established as a natural paragon for developing tactile sensors. So far, having object shape scanning and reconstruction in mind, almost all mechanical vibrissa models are restricted to contact scenarios with a single discrete contact force. Here, we deal with the effect of multi-point contacts in a specific scanning scenario, where an artificial vibrissa is swept along partly concave object contours. The vibrissa is modeled as a cylindrical, one-sided clamped Euler-Bernoulli bending rod undergoing large deflections. The elasticae and the support reactions during scanning are theoretically calculated and measured in experiments, using a spring steel wire, attached to a force/torque-sensor. The experiments validate the simulation results and show that the assumption of a quasi-static scanning displacement is a satisfying approach. Beyond single- and two-point contacts, a distinction is made between tip and tangential contacts. It is shown that, in theory, these contact phases can be identified solely based on the support reactions, what is new in literature. In this way, multipoint contacts are reliably detected and filtered in order to discard incorrectly reconstructed contact points.

In nature, there are several examples of sophisticated sensory systems to sense flows, e.g., the vibrissae of mammals. Seals can detect the flow of their prey, and rats are able to perceive the flow of surrounding air. The vibrissae are arranged around muzzle of an animal. A vibrissa consists of two major components: a shaft (infector) and a follicle–sinus complex (receptor), whereby the base of the shaft is supported by the follicle-sinus complex. The vibrissa shaft collects and transmits stimuli, e.g., flows, while the follicle-sinus complex transduces them for further processing. Beside detecting flows, the animals can also recognize the size of an object or determine the surface texture. Here, the combination of these functionalities in a single sensory system serves as paragon for artificial tactile sensors. The detection of flows becomes important regarding the measurement of flow characteristics, e.g., velocity, as well as the influence of the sensor during the scanning of objects. These aspects are closely related to each other, but, how can the characteristics of flow be represented by the signals at the base of a vibrissa shaft or by an artificial vibrissa-like sensor respectively? In this work, the structure of a natural vibrissa shaft is simplified to a slender, cylindrical/tapered elastic beam. The model is analyzed in simulation and experiment in order to identify the necessary observables to evaluate flows based on the quasi-static large deflection of the sensor shaft inside a steady, non-uniform, laminar, in-compressible flow.

Soft anthropomorphic robotic grippers are attractive because of their inherent compliance, allowing them to adapt to the shape of grasped objects and the overload protection needed for safe human–robot interaction or gripping delicate objects with sophisticated control. The anthropomorphic design allows the gripper to benefit from the biological evolution of the human hand to create a multi-functional robotic end effector. Entirely soft grippers could be more efficient because they yield under high loads. A trending solution is a hybrid gripper combining soft and rigid elements. This work describes a prototype of an anthropomorphic, underactuated five-finger gripper with a direct pneumatic drive from soft bending actuators and an integrated resistive tactile sensor array. It is a hybrid construction with soft robotic structures and rigid skeletal elements, which reinforce the body, focus the direction of the actuator’s movement, and make the finger joints follow the forward kinematics. The hand is equipped with a resistive tactile dielectric elastomer sensor array that directly triggers the hand’s actuation in the sense of reflexes. The hand can execute precision grips with two and three fingers, as well as lateral grip and strong grip types. The softness of the actuation allows the finger to adapt to the shape of the objects.

Rodents like rats and mice use their mystacial vibrissae for tactile perception. Several information of objects varying in (geometrical) size can be detected. For instance, the animals are able to recognize the shape of an object as well as to determine very fine surface textures by contacting the object with their vibrissae. The vibrissal kinematics differ in these tasks, the vibrissae can be brushed/swept against an object (protraction and retraction) or they can be dabbed against it. Here, a vibrissa inspired sensor (cylindrical spring steel wire) is swept along a rectangular object. Examining the influence of the displacement of the sensor support on the measured signals, translational and rotatory scanning scenarios are analyzed in simulations and experiments. In a first step, a frictionless contact between sensor and object is assumed. Then, friction is taken into account. In dependence on the scanning scenario the measured signal is amplified. Furthermore, the orientation of the sensor within one sweep is important in case of the frictional contact. The results imply that the scanning scenario and sensor orientation can be used to tune the measured signals.

This paper presents a soft gripper system in which actuation, sensing, and signal processing are all realized using soft dielectric elastomer (DE) devices. The platform integrates three functional units: a multilayer dielectric elastomer actuator (DEA) module that drives a compliant two-finger gripper, two tactile sensors mounted on the fingertips for contact detection and coarse shape recognition, and a dielectric elastomer switch (DES) that enables soft electronics control. The DEA module consists of eight parallel multilayer actuators, each comprising four active layers and a nonlinear biasing spring to amplify stroke, and is powered by an embedded high-voltage supply operated at 3 kV. The DES operates by mechanically modulating the resistance of a stretchable piezoresistive electrode, providing reliable switching behavior under high voltage. Grasping tests demonstrate that the system achieves a maximum opening angle of 38$^{\circ }$ and can safely manipulate delicate objects, including cherries and eggs, without damage. These results demonstrate the feasibility of advancing toward fully soft robotic systems by integrating DE-based components for actuation, sensing, and signal processing.