TacFlex: Multimode Tactile Imprints Simulation for Visuotactile Sensors With Coating Patterns
Chaofan Zhang, Shaowei Cui, Jingyi Hu, T. J. Jiang, Tiandong Zhang, Rui Wang, Shuo Wang
- Year
- 2025
- Citations
- 2
Abstract
Visuotactile sensors have been shown to provide rich contact information for robots. However, how to build a high-fidelity visuotactile simulator that supports multi-mode tactile imprints and various sensor configurations (such as coating patterns) remains a challenging problem. In this paper, we present TacFlex, an efficient and flexible simulator for visuotactile sensors, which physically simulates the elastomer deformation using Finite Element Methods (FEM), and focuses on linking the deformed elastomer mesh to diverse tactile imprints, including tactile images with arbitrary coating patterns and tactile 3D point clouds. We further propose a ray tracing-based rectification method to deal with multi-medium refraction effects to make the simulated tactile images more realistic. Extensive qualitative and quantitative experiments are conducted to demonstrate the effectiveness of TacFlex on several visuotactile sensors. Furthermore, we explore the Sim2Real performance of different tactile imprints provided by TacFlex in tactile perception and manipulation tasks, such as cylindrical object pose estimation and peg-in-hole. The perception/policy models trained in simulation are successfully deployed in the real world. Finally, we present the outlook on the potential of TacFlex in visuotactile manipulation learning. The TacFlex simulator is open-sourced to the community. See supplementary video, code, and results at <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://sites.google.com/view/tacflex/</uri>.
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