A soft thumb-sized vision-based sensor with accurate all-round force perception

TL;DR

This paper introduces Insight, a compact, vision-based tactile sensor that accurately perceives all-round 3D contact forces using a novel combination of photometric stereo, structured light, and deep learning, suitable for robotic applications.

Contribution

It presents the first soft, thumb-sized sensor combining photometric stereo and structured light with deep learning for precise 3D force mapping.

Findings

Force magnitude accuracy around 0.03 N

Force direction accuracy around 5 degrees

Spatial resolution of 0.4 mm

Abstract

Vision-based haptic sensors have emerged as a promising approach to robotic touch due to affordable high-resolution cameras and successful computer-vision techniques. However, their physical design and the information they provide do not yet meet the requirements of real applications. We present a robust, soft, low-cost, vision-based, thumb-sized 3D haptic sensor named Insight: it continually provides a directional force-distribution map over its entire conical sensing surface. Constructed around an internal monocular camera, the sensor has only a single layer of elastomer over-molded on a stiff frame to guarantee sensitivity, robustness, and soft contact. Furthermore, Insight is the first system to combine photometric stereo and structured light using a collimator to detect the 3D deformation of its easily replaceable flexible outer shell. The force information is inferred by a deep neural network that maps images to the spatial distribution of 3D contact force (normal and shear). Insight has an overall spatial resolution of 0.4 mm, force magnitude accuracy around 0.03 N, and force direction accuracy around 5 degrees over a range of 0.03--2 N for numerous distinct contacts with varying contact area. The presented hardware and software design concepts can be transferred to a wide variety of robot parts.