Adaptive Compressive Tactile Subsampling: Enabling High Spatiotemporal Resolution in Scalable Robotic Skin
Ariel Slepyan, Dian Li, Hongjun Cai, Ryan McGovern, Aidan Aug, Sriramana Sankar, Trac Tran, and Nitish Thakor

TL;DR
This paper introduces ACTS, a novel adaptive subsampling method that significantly increases the readout speed of tactile sensors, enabling real-time high-resolution tactile perception for robotics and wearable applications.
Contribution
The paper presents ACTS, a data-driven adaptive sampling technique that enhances tactile array performance by enabling high-speed, high-resolution tactile sensing with minimal reconstruction error.
Findings
Achieved up to 1,000 Hz frame rate on 1024-pixel tactile array
Enabled rapid object classification within 20 ms of contact
Demonstrated tactile-based closed-loop control for grasp stabilization
Abstract
Robots require full-body, high-resolution tactile sensing to operate safely in unstructured environments, enabling reflexive responses and closed-loop control. However, the pixel counts needed for dense, large-area coverage limit readout rates of most tactile arrays to <100 Hz, hindering their use in high-speed tasks. We present Adaptive Compressive Tactile Subsampling (ACTS), a scalable and data-driven method that greatly enhances traditional tactile matrices by leveraging adaptive sensor sampling and sparse recovery. By adaptively allocating measurements to informative regions, ACTS is especially effective for spatially sparse signals common in real-world interactions. 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…
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Taxonomy
TopicsTextile materials and evaluations · Tactile and Sensory Interactions · Industrial Vision Systems and Defect Detection
