DelTact: A Vision-based Tactile Sensor Using Dense Color Pattern

TL;DR

DelTact is a compact, high-resolution vision-based tactile sensor that uses an optimized dense color pattern and optical flow to accurately measure contact shape and force distribution in real-time.

Contribution

The paper introduces DelTact, a novel tactile sensor with a modular design, dense color pattern optimization, and real-time contact measurement capabilities.

Findings

High accuracy in contact deformation tracking

Low error tactile measurements at 40Hz

Effective extraction of contact shape and force distribution

Abstract

Tactile sensing is an essential perception for robots to complete dexterous tasks. As a promising tactile sensing technique, vision-based tactile sensors have been developed to improve robot performance in manipulation and grasping. Here we propose a new design of a vision-based tactile sensor, DelTact. The sensor uses a modular hardware architecture for compactness whilst maintaining a contact measurement of full resolution (798*586) and large area (675mm2). Moreover, it adopts an improved dense random color pattern based on the previous version to achieve high accuracy of contact deformation tracking. In particular, we optimize the color pattern generation process and select the appropriate pattern for coordinating with a dense optical flow algorithm under a real-world experimental sensory setting. The optical flow obtained from the raw image is processed to determine shape and force distribution on the contact surface. We also demonstrate the method to extract contact shape and force distribution from the raw images. Experimental results demonstrate that the sensor is capable of providing tactile measurements with low error and high frequency (40Hz).