A skin-like conformal sensor for real-time shape mapping

TL;DR

This paper presents a scalable, skin-like sensor that uses distributed strain gauges embedded in an elastomer to perform real-time 3D shape mapping of deformable surfaces, overcoming limitations of vision-based methods.

Contribution

It introduces a novel conformal sensor with embedded strain gauges and a mechanics-informed model for accurate, real-time 3D shape reconstruction in occlusion-prone environments.

Findings

Achieves a mean surface reconstruction error of 0.62 mm.

Operates with 0.1s latency across various deformation scenarios.

Successfully demonstrates applications in gesture, contact, and deformation monitoring.

Abstract

Reliable real-time 3D shape sensing is essential for robust control and interpretation of deformable systems during motion. Existing vision-based approaches require line-of-sight and complex instrumentation, limiting operation in occluded and space-constrained settings. Here, we introduce a scalable, skin-like sensor that reconstructs its continuous 3D deformation in real time from distributed strain measurements. The device embeds a 2D array of mirror-stacked, printed oxidized eutectic gallium-indium (o-EGaIn) strain gauges within an elastomeric film to measure off-neutral-axis strains. Combined with a mechanics-informed observation model and a fast optimization routine, the system estimates local curvature, elongation, offset, and orientation under concurrent stretching, bending, and indentation, enabling reconstruction of complex surfaces. A 5-by-5 array with a 12 mm pitch achieves a mean surface reconstruction error of 0.62 mm with 0.1s latency across all tested scenarios. When conforming to complex surfaces, the sensor provides fast 3D shape mapping of the underlying geometry. Demonstrations involving palm gesturing, finger indentation, and contact-induced balloon deformation highlight utility for epidermal motion tracking, haptic interaction, and intraoperative monitoring.