AllSight: A Low-Cost and High-Resolution Round Tactile Sensor with Zero-Shot Learning Capability

Abstract

Tactile sensing is a necessary capability for a robotic hand to perform fine manipulations and interact with the environment. Optical sensors are a promising solution for high-resolution contact estimation. Nevertheless, they are usually not easy to fabricate and require individual calibration in order to acquire sufficient accuracy. In this letter, we propose AllSight, an optical tactile sensor with a round 3D structure potentially designed for robotic in-hand manipulation tasks. AllSight is mostly 3D printed making it low-cost, modular, durable and in the size of a human thumb while with a large contact surface. We show the ability of AllSight to learn and estimate a full contact state, i.e., contact position, forces and torsion. With that, an experimental benchmark between various configurations of illumination and contact elastomers are provided. Furthermore, the robust design of AllSight provides it with a unique zero-shot capability such that a practitioner can fabricate the open-source design and have a ready-to-use state estimation model. A set of experiments demonstrates the accurate state estimation performance of AllSight.

References in corpus (5)

• DIGIT: A Novel Design for a Low-Cost Compact High-Resolution Tactile Sensor with Application to In-Hand Manipulation
• TACTO: A Fast, Flexible, and Open-source Simulator for High-Resolution Vision-based Tactile Sensors
• A Sensorized Multicurved Robot Finger with Data-driven Touch Sensing via Overlapping Light Signals
• Learning Haptic-based Object Pose Estimation for In-hand Manipulation Control with Underactuated Robotic Hands
• Learning to Read Braille: Bridging the Tactile Reality Gap with Diffusion Models

Cited by in corpus (2)

• ThinTact:Thin Vision-Based Tactile Sensor by Lensless Imaging
• A Survey of Embodied Learning for Object-Centric Robotic Manipulation