A machine learning framework developed by researchers at the University of Maryland (UMD) aims to accelerate the design of soft machines.
The framework can be used to build a prediction model that perform the two-way design task, predicting sensor performance based on a fabrication recipe and recommending feasible fabrication recipes for adequate strain sensors.
UMD's Po-Yen Chen said, "What we've essentially created is a high-accuracy prediction software – based on a machine learning framework – capable of designing a wide range of strain sensors that can be integrated into diverse soft machines."
From University of Maryland A. James Clark School of Engineering
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