Elastomer composites have proven to be promising functional materials for soft actuators. Direct manufacturing of these materials is a practical prerequisite for Soft Robotics applications, where form and function are intricately entangled. In this article we show a multimaterial printer and associated processes for in situ fabrication of silicones and silicone-based elastomer composites for soft actuators. We discuss the fabrication process for both the silicone/ethanol composite material and encapsulating silicone skin using an inline passive mixing system, followed by characterization of the rheological and mechanical properties of the printed materials for various print modalities. Rheological study revealed the conditions, allowing continuous 3D printing of both small and big items out of silicone rubber and silicone/ethanol composite. Anisotropic mechanical properties allow for the design of functional characteristics of soft actuators by choosing print design modalities. We demonstrate a single-print-job additive manufacturing of functional multimaterial systems for soft actuation, and suggest that the developed processes will allow us to design soft robots with a broad range of actuation characteristics.

We examine electrically conductive fabrics as conductive heaters for heat-activated soft actuators. We have explored various fabric designs optimized for material properties, heat distribution and actuation/de-actuation characteristics of the soft actuators. We implemented this approach in the silicone/ethanol composite actuators, in which ethanol undergoes a thermally-induced phase change, leading to high actuation stress and strain. Various types of conductive fabrics were tested, and we developed a stretchable kirigami-based fabric design. We demonstrate a fabric heater that is capable of cyclic heating of the actuator to the required 80 °C. The fabric with the special kirigami design can withstand temperatures of up to 195 °C, can consume up to 30 W of power, and allows the actuator to reach >30% linear strain. This technology may be used in various systems involving thermally-induced actuation.

The actuation of silicone/ethanol soft composite material-actuators is based on the phase change of ethanol upon heating, followed by the expansion of the whole composite, exhibiting high actuation stress and strain. However, the low thermal conductivity of silicone rubber hinders uniform heating throughout the material, creating overheated damaged areas in the silicone matrix and accelerating ethanol evaporation. This limits the actuation speed and the total number of operation cycles of these thermally-driven soft actuators. In this paper, we showed that adding 8 wt.% of diamond nanoparticle-based thermally conductive filler increases the thermal conductivity (from 0.190 W/mK to 0.212 W/mK), actuation speed and amount of operation cycles of silicone/ethanol actuators, while not affecting the mechanical properties. We performed multi-cyclic actuation tests and showed that the faster and longer operation of 8 wt.% filler material-actuators allows collecting enough reliable data for computational methods to model further actuation behavior. We successfully implemented a long short-term memory (LSTM) neural network model to predict the actuation force exerted in a uniform multi-cyclic actuation experiment. This work paves the way for a broader implementation of soft thermally-driven actuators in various robotic applications.

Virtual reality (VR) is a useful tool to assess and improve spatial navigation, a complex skill and relevant marker for progression of dementia. A fully-immersive VR system that allows the user to physically navigate in the space can provide an ecologically valid environment for early detection and remediation of cognitive and navigational deficits. The aim of this study was to develop a virtual version of the floor maze test (VR-FMT), a navigational test that requires navigating through an unfamiliar two-dimensional floor maze. With the VR-FMT, mazes of desired complexity and walls of preferred height can be built to challenge navigational ability and mask visual clues. Fifty-five healthy adults completed the FMT in three different conditions: real environment (RE), virtual environment with no walls (VE-NW), and virtual environment with walls (VE-W). In addition, they completed two neuropsychological tests, the Trail Making Test and Digit Symbol Substitution Test. Results showed that the time to complete the maze in the VE was significantly higher than in the RE. The introduction of walls increased the number of errors, the completion time, and the length of the path. Only time to exit in the VE-W correlated with results of the cognitive tests. Participants were further subdivided on the basis of their time to exit the maze in the RE, VE-NW, and VE-W (low navigational time -LNT, and high navigational time -HNT). Only when analyzing the time to exit the maze in the VE-W, the LNT group outperformed the HNT group in all cognitive tests.

We present an open-source untethered quadrupedal soft robot platform for dynamic locomotion (e.g., high-speed running and backflipping). The robot is mostly soft (80 vol.%) while driven by four geared servo motors. The robot's soft body and soft legs were 3D printed with gyroid infill using a flexible material, enabling it to conform to the environment and passively stabilize during locomotion on multi-terrain environments. In addition, we simulated the robot in a real-time soft body simulation. With tuned gaits in simulation, the real robot can locomote at a speed of 0.9 m/s (2.5 body length/second), substantially faster than most untethered legged soft robots published to date. We hope this platform, along with its verified simulator, can catalyze the development of soft robotics.