Taccel: Scaling Up Vision-based Tactile Robotics via High-performance GPU Simulation
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Abstract (arXiv)
Tactile sensing is crucial for achieving human-level robotic capabilities in manipulation tasks. As a promising solution, Vision-Based Tactile Sensors (VBTSs) offer high spatial resolution and cost-effectiveness, but present unique challenges in robotics for their complex physical characteristics and visual signal processing requirements. The lack of efficient and accurate simulation tools for VBTSs has significantly limited the scale and scope of tactile robotics research. 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, potentially transforming how robots interact with and understand their physical environment.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 36 of its 69 references that are in the map. First posted on arXiv 17 Apr 2025.
Builds on
36 of 69 references.
References · 36
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24 more
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- 2021Taxim: An Example-based Simulation Model for GelSight Tactile Sensorscited by 42
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- 2023Visual-Tactile Sensing for In-Hand Object Reconstructioncited by 13
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Built on by
Citing papers per year: 2025: 3; 2026: 3.
6 papers.
- 2025A Survey of Robotic Navigation and Manipulation with Physics Simulators in the Era of Embodied AIcited by 16
- 2025Simultaneous Tactile-Visual Perception for Learning Multimodal Robot Manipulationcited by 6
- 2026Data Pyramid for Embodied Manipulation: A Surveycited by 4
- 2026TacCoRL: Integrating Tactile Feedback into VLA via Simulationcited by 3
- 2026Blind Dexterous Grasping via Real2Sim2Real Tactile Policy Learningcited by 3
- 2025ControlTac: Scaling Tactile Data with Physically Controlled Tactile Image Generationcited by 0
- 2026Data Pyramid for Embodied Manipulation: A Survey27 Jul 2026
- 2026Blind Dexterous Grasping via Real2Sim2Real Tactile Policy Learning10 Jun 2026
- 2026TacCoRL: Integrating Tactile Feedback into VLA via Simulation10 Jun 2026
- 2025Simultaneous Tactile-Visual Perception for Learning Multimodal Robot Manipulation10 Dec 2025
- 2025ControlTac: Scaling Tactile Data with Physically Controlled Tactile Image Generation26 May 2025
- 2025A Survey of Robotic Navigation and Manipulation with Physics Simulators in the Era of Embodied AI1 May 2025