Taccel: Scaling Up Vision-based Tactile Robotics via High-performance GPU Simulation
🤖 AI Summary
Visual-tactile sensor (VBTS) simulation has long suffered from low-fidelity physical modeling, poor computational efficiency, and limited parallel scalability, hindering large-scale development of tactile robotics. To address these challenges, we present the first high-performance GPU-accelerated VBTS simulation platform. Our method uniquely integrates the Implicit Contact (IPC) framework for robust continuum mechanics with an Adaptive Boundary Dynamics (ABD) engine, enabling 18× real-time performance at thousand-level GPU parallelism. The platform supports configurable robot–sensor systems, high-fidelity elastic gel deformation rendering, and end-to-end generation of photorealistic tactile image signals. We validate its accuracy and sim-to-real transferability across object recognition, grasping, and articulated manipulation tasks. Results demonstrate substantial improvements in tactile policy training efficiency and real-world deployment feasibility.
Application Category
📝 Abstract
Tactile sensing is crucial for achieving human-level robotic capabilities in manipulation tasks. VBTSs have emerged as a promising solution, offering high spatial resolution and cost-effectiveness by sensing contact through camera-captured deformation patterns of elastic gel pads. However, these sensors' complex physical characteristics and visual signal processing requirements present unique challenges for robotic applications. The lack of efficient and accurate simulation tools for VBTS has significantly limited the scale and scope of tactile robotics research. Here we present Taccel, a high-performance simulation platform that integrates IPC and ABD to model robots, tactile sensors, and objects with both accuracy and unprecedented speed, achieving an 18-fold acceleration over real-time across thousands of parallel environments. Unlike previous simulators that operate at sub-real-time speeds with limited parallelization, Taccel provides precise physics simulation and realistic tactile signals while supporting flexible robot-sensor configurations through user-friendly APIs. Through extensive validation in object recognition, robotic grasping, and articulated object manipulation, we demonstrate precise simulation and successful sim-to-real transfer. These capabilities position Taccel as a powerful tool for scaling up tactile robotics research and development. By enabling large-scale simulation and experimentation with tactile sensing, Taccel accelerates the development of more capable robotic systems, potentially transforming how robots interact with and understand their physical environment.
Problem
Research questions and friction points this paper is trying to address.
Lack of efficient VBTS simulation tools limits tactile robotics research.
VBTS sensors pose challenges in physical modeling and visual processing.
Existing simulators are slow and lack parallelization for tactile applications.
Innovation
Methods, ideas, or system contributions that make the work stand out.
High-performance GPU simulation for tactile robotics
Integrates IPC and ABD for accurate, fast modeling
Supports large-scale parallel environments with real-time speed
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