Whole-body-contact sensing will be crucial in the quest to make robots capable of safe interaction with humans. This paper describes a novel design and a fabrication method of artificial tactile sensing skin for robots. The manufacturing method described in this paper allows easy filling of a complex microchannel network with a liquid conductor (e.g., room temperature ionic liquid (RTIL)). The proposed sensing skin can detect the magnitude and location of surface contacts using electrical impedance tomography (EIT), an imaging technique mostly used in the medical field and examined recently in conjunction with sensors based on a piezoresistive polymer sheet for robotic applications. Unlike piezoresistive polymers, our IL-filled artificial skin changes its impedance in a more predictable manner, since the measured value is determined by a simple function of the microchannel geometry only, rather than complex physical phenomena. As a proof of concept, we demonstrate that our EIT artificial skin can detect surface contacts and graphically show their magnitudes and locations.
The cross-sectional geometry of an embedded microchannel influences the electromechanical response of a soft microfluidic sensor to applied surface pressure. When a pressure is exerted on the surface of the sensor deforming the soft structure, the cross-sectional area of the embedded channel filled with a conductive fluid decreases, increasing the channel's electrical resistance. This electromechanical coupling can be tuned by adding solid microspheres into the channel. In order to determine the influence of microspheres, we use both analytic and computational methods to predict the pressure responses of soft microfluidic sensors with two different channel cross-sections: a square and an equilateral triangular. The analytical models were derived from contact mechanics in which microspheres were regarded as spherical indenters, and finite element analysis (FEA) was used for simulation. For experimental validation, sensor samples with the two different channel cross-sections were prepared and tested. For comparison, the sensor samples were tested both with and without microspheres. All three results from the analytical models, the FEA simulations, and the experiments showed reasonable agreement confirming that the multi-material soft structure significantly improved its pressure response in terms of both linearity and sensitivity. The embedded solid particles enhanced the performance of soft sensors while maintaining their flexible and stretchable mechanical characteristic. We also provide analytical and experimental analyses of hysteresis of microfluidic soft sensors considering a resistive force to the shape recovery of the polymer structure by the embedded viscous fluid.
Biological organisms demonstrate remarkable agility in complex environments, especially in comparison to engineered robotic systems. In part, this is due to an organism's ability to detect disturbances and react to them quickly. To address the challenge of quickly sensing these same disturbances in robotic systems, this study proposes and demonstrates large‐area soft sensing skins designed to sense disturbances on unmanned aerial vehicles (UAVs) in flight. These skins are enabled by high‐resolution soft strain sensors embedded into a large‐area skin through a modular molding process that spans feature sizes from tens of microns to 0.675 m. The electronics of the sensing system enable the soft skins to be sampled fast enough to capture dynamic loads on a wing. Overall, the large‐area soft sensing skin demonstrates high sensitivity, mechanical robustness, and consistent sensor readings across static and dynamic tests. The use of the soft sensing skin during UAV flight demonstrates that the sensing skin can capture relevant flight dynamics on small UAVs. These results pave the way to large‐area soft sensing skins for fast and robust control of a wide variety of robotic systems.
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