Tacchi 2.0: A Low Computational Cost and Comprehensive Dynamic Contact Simulator for Vision-based Tactile Sensors
This work addresses the durability and cost issues in tactile data acquisition for robotics, offering a low-cost simulation tool, though it is incremental as an upgrade to an existing simulator.
The authors tackled the high cost and computational demands of generating tactile data for vision-based sensors by developing Tacchi 2.0, a simulator that integrates a pinhole camera model with the Material Point Method to produce tactile, marker motion, and joint images under various contact states, achieving reliability and robustness across different sensors.
With the development of robotics technology, some tactile sensors, such as vision-based sensors, have been applied to contact-rich robotics tasks. However, the durability of vision-based tactile sensors significantly increases the cost of tactile information acquisition. Utilizing simulation to generate tactile data has emerged as a reliable approach to address this issue. While data-driven methods for tactile data generation lack robustness, finite element methods (FEM) based approaches require significant computational costs. To address these issues, we integrated a pinhole camera model into the low computational cost vision-based tactile simulator Tacchi that used the Material Point Method (MPM) as the simulated method, completing the simulation of marker motion images. We upgraded Tacchi and introduced Tacchi 2.0. This simulator can simulate tactile images, marked motion images, and joint images under different motion states like pressing, slipping, and rotating. Experimental results demonstrate the reliability of our method and its robustness across various vision-based tactile sensors.