Tightly integrating sensing, actuation, and computation into composites could enable a new generation of truly smart material systems that can change their appearance and shape autonomously. Applications for such materials include airfoils that change their aerodynamic profile, vehicles with camouflage abilities, bridges that detect and repair damage, or robotic skins and prosthetics with a realistic sense of touch. Although integrating sensors and actuators into composites is becoming increasingly common, the opportunities afforded by embedded computation have only been marginally explored. Here, the key challenge is the gap between the continuous physics of materials and the discrete mathematics of computation. Bridging this gap requires a fundamental understanding of the constituents of such robotic materials and the distributed algorithms and controls that make these structures smart.

We present a composite material consisting of a thermoplastic base material and embedded, networked sensing, actuation, and control to vary its stiffness locally based on computational logic. A polycaprolactone grid provides stiffness at room temperature. Each polycaprolactone element within the grid is equipped with a dedicated heating element, thermistor, and networked microcontroller that can drive the element to a desired temperature/stiffness. We present experimental results using a 4 × 1 grid that can assume different global conformations under the influence of gravity by simply changing the local stiffness of individual parts. We describe the composite structure and its manufacturing, the principles behind variable stiffness control using Joule heating, local sliding mode control of each polycaprolactone bar’s temperature and function, and limitations of the embedded multi-hop communication system. The function of the local temperature controller is evaluated experimentally.

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