An important aspect of soft robotics, next to the different actuation mechanisms, is the monitoring of the robot's position and condition and, thus, the local and global strains via integrated sensors. Currently investigated actuation classes and materials like dielectric elastomer actuators or twisted-coiled polymeric actuators offer large strain potentials, rendering conventional metal or semiconductor strain gauges unsuitable. [3] Apart from their inherent strain limit of less than 5%, the difficult integration into and adhesion to smart materials is preventing their use in novel complex and compact soft robots. [4,5] Additionally, as some of the currently researched actuator mechanisms and principles offer high strain rate actuation, the necessity of not only a quasistatic but also dynamic monitoring and suitable control strategies is conspicuous. One approach to integrate actuators and sensors and to achieve resilient but flexible structures is using fiber-shaped active materials similar to muscles and nerves in biological systems. [6] A popular choice as a sensor material are carbon-based particle-filled highly stretchable elastomers (CPFEs). Such particles can be carbon black (CB), carbon nanotubes (CNT), graphene, or combinations thereof. Until today, there has been a vast amount of studies investigating different polymer materials, fillers, and mixing ratios as well as their applications to monitor soft robots or body posture. [7,8] Additionally, the conducting particles can also be used in order to tailor the electro-thermal response of shape memory polymers. [9] The standard analysis performed to evaluate the different soft sensor systems is a quasistatic tensile test while tracking the resistance. Investigations of dynamic sensor properties with systematically varied strain rates and loading scenarios are scarce. This lack of data also contributes to the poorly understood phenomena occurring during cyclic, dynamic loading of CPFEs. [10] To employ CPFEs as sensors, their linearity, sensitivity, and monotonicity are important features. [11] Unfortunately, the few investigations so far on dynamic mechano-electrical properties show non-monotonic responses, meaning that, apart from the resistance peak at maximum strain, additional peaks occur. [12,13,14] These peaks either appear while releasing or when the imposed strain is fully released and have been called shoulder phenomenon or secondary peaks. The phenomenon appears independently whether the filler material is CB, CNT, or graphene. [11,15,16] To distinguish between the different phenomena described in literature, the nomenclature in Figure 1 Carbon particle-filled polymers are frequently used as stretchable conductors and strain sensors. Many of the proposed resistance-based stretchable strain sensors show non-monotonic strain response, especially under dynamic conditions. This is commonly attributed to the competing destruction and reformation of the conductive network, but the underlying mechanism is still unknown. Therefore, systematic cyclic tens...

The concept of merging pre-processed textile materials with tailored mechanical properties into soft matrices is so far rarely used in the field of soft robotics. The herein presented work takes the advantages of textile materials in elastomer matrices to another level by integrating a material with highly anisotropic bending properties. A pre-fabricated textile material consisting of oriented carbon fibers is used as a stiff component to precisely control the mechanical behavior of the robotic setup. The presented robotic concept uses a multi-layer stack for the robot’s body and dielectric elastomer actuators (DEAs) on both outer sides of it. The bending motion of the whole structure results from the combination of its mechanically adjusted properties and the force generation of the DEAs. We present an antagonistic switching setup for the DEAs that leads to deflections to both sides of the robot, following a biomimetic principle. To investigate the bending behavior of the robot, we show a simulation model utilizing electromechanical coupling to estimate the quasi-static deflection of the structure. Based on this model, a statement about the bending behavior of the structure in general is made, leading to an expected maximum deflection of 10 mm at the end of the fin for a static activation. Furthermore, we present an electromechanical network model to evaluate the frequency dependent behavior of the robot’s movement, predicting a resonance frequency of 6.385 Hz for the dynamic switching case. Both models in combination lead to a prediction about the acting behavior of the robot. These theoretical predictions are underpinned by dynamic performance measurements in air for different switching frequencies of the DEAs, leading to a maximum deflection of 9.3 mm located at the end of the actuators. The herein presented work places special focus on the mechanical resonance frequency of the robotic setup with regard to maximum deflections.

For soft robotics, shape memory alloy (SMA)‐based elastomeric actuators are a promising material combination but their maximum stroke is limited by the small inherent contraction of SMAs. In this work, a textile‐reinforced soft actuator is presented, which has additional SMA wire length included in the textile structure as well as a sensoric textile to track the actuator's pose. This strategy eliminates the need for external SMA wires with extra mechanical components. Various experiments with different excitation voltages are performed to show the actuator's performance. In a horizontal setup, the soft actuator reaches a bending angle of 270° at a power input of 18 W. The integrated sensor reflects the actuator's position but is also influenced by the temperature increase during activation. Moreover, an equivalent circuit model is proposed that includes the actuator, sensor, and mechanical support structure in one model. The model incorporates not only the mechanical but also the thermal and electrical domains. The simulation results are in good agreement with the experimental results.

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Soft actuators are a promising option for the advancing fields of human-machine interaction and dexterous robots in complex environments. Shape memory alloy wire actuators can be integrated into fiber rubber composites for highly deformable structures. For autonomous, closed-loop control of such systems, additional integrated sensors are necessary. In this work, a soft actuator is presented that incorporates fiber-based actuators and sensors to monitor both deformation and temperature. The soft actuator showed considerable deformation around two solid body joints, which was then compared to the sensor signals, and their correlation was analyzed. Both, the actuator as well as the sensor materials were processed by braiding and tailored fiber placement before molding with silicone rubber. Finally, the novel fiber-rubber composite material was used to implement closed-loop control of the actuator with a maximum error of 0.5°.