Elastic Interaction of Particles for Robotic Tactile Simulation

TL;DR

This paper introduces EIP, a novel particle-based framework for simulating elastic tactile interactions in robotics, enabling more realistic tactile data generation and 3D reconstruction without relying on existing physics engines.

Contribution

EIP models tactile sensors as coordinated particles regulated by elastic theory, providing a new approach for realistic tactile simulation in robotics.

Findings

Effective tactile perception with simulated data

Improved 3D geometric reconstruction accuracy

Potential for enhanced robotic manipulation tasks

Abstract

Tactile sensing plays an important role in robotic perception and manipulation. To overcome the real-world limitations of data collection, simulating tactile response in virtual environment comes as a desire direction of robotic research. Most existing works model the tactile sensor as a rigid multi-body, which is incapable of reflecting the elastic property of the tactile sensor as well as characterizing the fine-grained physical interaction between two objects. In this paper, we propose Elastic Interaction of Particles (EIP), a novel framework for tactile emulation. At its core, EIP models the tactile sensor as a group of coordinated particles, and the elastic theory is applied to regulate the deformation of particles during the contact process. The implementation of EIP is conducted from scratch, without resorting to any existing physics engine. Experiments to verify the effectiveness of our method have been carried out on two applications: robotic perception with tactile data and 3D geometric reconstruction by tactile-visual fusion. It is possible to open up a new vein for robotic tactile simulation, and contribute to various downstream robotic tasks.