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Tac3D: A Novel Vision-based Tactile Sensor for Measuring Forces Distribution and Estimating Friction Coefficient Distribution
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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.
Forward citations
Cited by 5 Pith papers
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CoorGrasp: Coordinated Contact Control for Adaptive Dexterous Grasping Under Uncertainty
CoorGrasp's MPC with coordination-aware phase separation, arm-hand adjustment, and adaptive force allocation raises grasp success and cuts in-hand object motion versus open-loop and independent-finger baselines on 15k...
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LightTact: A Visual-Tactile Fingertip Sensor for Deformation-Independent Contact Sensing
A fingertip camera sensor uses a light-blocking wedge so that only true contact pixels brighten, enabling deformation-free contact detection with liquids, soft materials, and rigid objects.
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Classification of Vision-Based Tactile Sensors: A Review
A review that proposes a four-type classification of vision-based tactile sensors, dividing them into marker-based versus intensity-based transduction with subtypes and combinations.
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T-Rex: Task-Adaptive Spatial Representation Extraction for Robotic Manipulation with Vision-Language Models
A zero-training framework that adaptively selects spatial representation extractors per object and per task stage improves real-world robot manipulation success and efficiency over fixed-representation baselines.
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Universal Visuo-Tactile Video Understanding for Embodied Interaction
VTV-LLM is a tactile-video large language model, trained on a new VTV150K dataset, that reasons about hardness, protrusion, elasticity, and friction in natural language.
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