Adaptive Compressive Tactile Subsampling: Enabling High Spatiotemporal Resolution in Scalable Robotic Skin (2410.13847v2)

Abstract: Robots, like humans, require full-body, high-resolution tactile sensing to operate safely and effectively in unstructured environments, enabling reflexive responses and closed-loop control. However, the high pixel counts necessary for dense, large-area coverage limit readout rates of most tactile arrays to below 100 Hz, hindering their use in high-speed tasks. We introduce Adaptive Compressive Tactile Subsampling (ACTS), a scalable and data-driven method that dramatically enhances the performance of traditional tactile matrices by leveraging sparse recovery and a learned tactile dictionary. Tested on a 1024-pixel tactile sensor array (32X32), ACTS achieved frame rates up to 1,000 Hz, an 18X improvement over conventional raster scanning, with minimal reconstruction error. For the first time, ACTS enables wearable, large-area, high-density tactile sensing systems that can deliver high-speed results. We demonstrate rapid object classification within 20 ms of contact, high-speed projectile detection, ricochet angle estimation, and soft deformation tracking, in tactile and robotics applications, all using flexible, high-density tactile arrays. These include high-resolution tactile gloves, pressure insoles, and full-body configurations covering robotic arms and human-sized mannequins. ACTS transforms standard, low-cost, and robust tactile sensors into high-speed systems, supporting applications from object manipulation to human-robot interaction. By enabling comprehensive, scalable, and efficient tactile coverage for robots and wearables, ACTS advances robotics toward lifelike, responsive, and adaptable operation in dynamic environments.