Tac3D: A Novel Vision-based Tactile Sensor for Measuring Forces Distribution and Estimating Friction Coefficient Distribution
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Abstract (arXiv)
The importance of force perception in interacting with the environment was proven years ago. However, it is still a challenge to measure the contact force distribution accurately in real-time. In order to break through this predicament, we propose a new vision-based tactile sensor, the Tac3D sensor, for measuring the three-dimensional contact surface shape and contact force distribution. In this work, virtual binocular vision is first applied to the tactile sensor, which allows the Tac3D sensor to measure the three-dimensional tactile information in a simple and efficient way and has the advantages of simple structure, low computational costs, and inexpensive. Then, we used contact surface shape and force distribution to estimate the friction coefficient distribution in contact region. Further, combined with the global position of the tactile sensor, the 3D model of the object with friction coefficient distribution is reconstructed. These reconstruction experiments not only demonstrate the excellent performance of the Tac3D sensor but also imply the possibility to optimize the action planning in grasping based on the friction coefficient distribution of the object.
Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). First posted on arXiv 13 Feb 2022.
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Citing papers per year: 2023: 2; 2024: 2; 2025: 3; 2026: 4.
11 papers.
- 2025AnyTouch: Learning Unified Static-Dynamic Representation across Multiple Visuo-tactile Sensorscited by 46
- 2023The Power of the Senses: Generalizable Manipulation from Vision and Touch through Masked Multimodal Learningcited by 24
- 2025Universal Visuo-Tactile Video Understanding for Embodied Interactioncited by 7
- 2024Learning Force Distribution Estimation for the GelSight Mini Optical Tactile Sensor Based on Finite Element Analysiscited by 4
- 2023GelFlow: Self-supervised Learning of Optical Flow for Vision-Based Tactile Sensor Displacement Measurementcited by 2
- 2026Tactile-based Multimodal Fusion in Embodied Intelligence: A Survey of Vision, Language, and Contact-Driven Paradigmscited by 2
- 2024Learning Gentle Grasping from Human-Free Force Control Demonstrationcited by 1
- 2025T-Rex: Task-Adaptive Spatial Representation Extraction for Robotic Manipulation with Vision-Language Modelscited by 1
- 2026OmniVaT: Single Domain Generalization for Multimodal Visual-Tactile Learningcited by 0
- 2026Touch-R1: Reinforcing Touch Reasoning in MLLMscited by 0
- 2026DeCAL: Towards Physically-Grounded Dexterous Vision-Language-Action Models via Contact-Aware Latent Co-Imaginationcited by 0
- 2026DeCAL: Towards Physically-Grounded Dexterous Vision-Language-Action Models via Contact-Aware Latent Co-Imagination8 Sep 2026
- 2026Touch-R1: Reinforcing Touch Reasoning in MLLMs26 May 2026
- 2026Tactile-based Multimodal Fusion in Embodied Intelligence: A Survey of Vision, Language, and Contact-Driven Paradigms17 May 2026
- 2026OmniVaT: Single Domain Generalization for Multimodal Visual-Tactile Learning1 Jan 2026
- 2025T-Rex: Task-Adaptive Spatial Representation Extraction for Robotic Manipulation with Vision-Language Models24 Jun 2025
- 2025Universal Visuo-Tactile Video Understanding for Embodied Interaction28 May 2025
- 2025AnyTouch: Learning Unified Static-Dynamic Representation across Multiple Visuo-tactile Sensors15 Feb 2025
- 2024Learning Force Distribution Estimation for the GelSight Mini Optical Tactile Sensor Based on Finite Element Analysis8 Oct 2024
- 2024Learning Gentle Grasping from Human-Free Force Control Demonstration16 Sep 2024
- 2023The Power of the Senses: Generalizable Manipulation from Vision and Touch through Masked Multimodal Learning2 Nov 2023
- 2023GelFlow: Self-supervised Learning of Optical Flow for Vision-Based Tactile Sensor Displacement Measurement13 Sep 2023