Integrated Pneumatic Sensing and Actuation for Soft Haptic Devices

We present an integrated pneumatic sensor and actuator for soft haptic devices that can estimate contact force, location, and shape using a multi-headed neural network. The sensor uses channels cast into a multi-layer silicone bubble that change flow resistance as the bubble deforms, allowing measurements of strain and external contact at the surface. Changes in flow resistance are measured using pressure transducers in a pneumatic circuit. Arranging the channels in a two-layer array allows localization of the strain with an accuracy of over 80% for contact locations in a 3×3 grid and force measurements from 0.9–4.5 N with an RMS error of $\approx$ 0.39 N. This technology can enable closed-loop control for future soft pneumatic devices.