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Found 5 papers, 2 papers with code
TouchSDF: A DeepSDF Approach for 3D Shape Reconstruction using Vision-Based Tactile Sensing
To address these challenges, we propose TouchSDF, a Deep Learning approach for tactile 3D shape reconstruction that leverages the rich information provided by a vision-based tactile sensor and the expressivity of the implicit neural representation DeepSDF.
Attention for Robot Touch: Tactile Saliency Prediction for Robust Sim-to-Real Tactile Control
To improve the robustness of tactile robot control in unstructured environments, we propose and study a new concept: \textit{tactile saliency} for robot touch, inspired by the human touch attention mechanism from neuroscience and the visual saliency prediction problem from computer vision.
Semi-Supervised Disentanglement of Tactile Contact~Geometry from Sliding-Induced Shear
The sense of touch is fundamental to human dexterity.
Tactile Sim-to-Real Policy Transfer via Real-to-Sim Image Translation
Simulation has recently become key for deep reinforcement learning to safely and efficiently acquire general and complex control policies from visual and proprioceptive inputs.
Deep Reinforcement Learning for Tactile Robotics: Learning to Type on a Braille Keyboard
Artificial touch would seem well-suited for Reinforcement Learning (RL), since both paradigms rely on interaction with an environment.
