SandWorm: Event-based Visuotactile Perception with Active Vibration for Screw-Actuated Robot in Granular Media

TL;DR

SandWorm is a biomimetic robot equipped with a novel event-based visuotactile sensor, SWTac, capable of high-resolution tactile imaging and force estimation, enabling effective locomotion and exploration in challenging granular terrains.

Contribution

This work introduces SWTac, a vibration-optimized event-based tactile sensor, and demonstrates its integration with SandWorm for enhanced perception and locomotion in granular media.

Findings

SWTac achieves 0.2 mm texture resolution.

98% accuracy in stone classification.

0.15 N force estimation error.

Abstract

Perception in granular media remains challenging due to unpredictable particle dynamics. To address this challenge, we present SandWorm, a biomimetic screw-actuated robot augmented by peristaltic motion to enhance locomotion, and SWTac, a novel event-based visuotactile sensor with an actively vibrated elastomer. The event camera is mechanically decoupled from vibrations by a spring isolation mechanism, enabling high-quality tactile imaging of both dynamic and stationary objects. For algorithm design, we propose an IMU-guided temporal filter to enhance imaging consistency, improving MSNR by 24%. Moreover, we systematically optimize SWTac with vibration parameters, event camera settings and elastomer properties. Motivated by asymmetric edge features, we also implement contact surface estimation by U-Net. Experimental validation demonstrates SWTac's 0.2 mm texture resolution, 98% stone classification accuracy, and 0.15 N force estimation error, while SandWorm demonstrates versatile locomotion (up to 12.5 mm/s) in challenging terrains, successfully executes pipeline dredging and subsurface exploration in complex granular media (observed 90% success rate). Field experiments further confirm the system's practical performance.