Soft Surfaced Vision-Based Tactile Sensing for Bipedal Robot Applications

TL;DR

This paper introduces a soft, vision-based tactile sensor for bipedal robots that enhances balance and terrain understanding by capturing contact deformations optically, enabling richer perception during locomotion.

Contribution

It presents a novel soft-surfaced, vision-based tactile foot sensor that estimates contact pose, visualizes shear, and classifies terrain, improving robot stability and environmental awareness.

Findings

Tactile feedback improves balance control.

Sensor accurately estimates contact pose and shear.

Enhances terrain classification and contact feature detection.

Abstract

Legged locomotion benefits from embodied sensing, where perception emerges from the physical interaction between body and environment. We present a soft-surfaced, vision-based tactile foot sensor that endows a bipedal robot with a skin-like deformable layer that captures contact deformations optically, turning foot-ground interactions into rich haptic signals. From a contact image stream, our method estimates contact pose (position and orientation), visualizes shear, computes center of pressure (CoP), classifies terrain, and detects geometric features of the contact patch. We validate these capabilities on a tilting platform and in visually obscured conditions, showing that foot-borne tactile feedback improves balance control and terrain awareness beyond proprioception alone. These findings suggest that integrating tactile perception into legged robot feet improves stability, adaptability, and environmental awareness, offering a promising direction toward more compliant and intelligent locomotion systems. For the supplementary video, please visit: https://youtu.be/ceJiy9q_2Aw