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Tactile RL
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2026-03-03 14:40:48
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TactileRL Sim2Real Manipulation on Unknown Objects with Tactile-based Reinforcement Learning ICRA 2024 Paper Entong Su , Chengzhe Jia* , Yuzhe Qin* , Wenxuan Zhou* , Annabella Macaluso* , Binghao Huang , Xiaolong Wang , Abstract Using Tactile sensors for manipulation remains as one of the most challenging problems in robotics. At the heart of these challenges is generalization: How can we train a tactile-based policy that can manipulate unseen and diverse objects? In this paper, we propose to perform Reinforcement Learning with only visual tactile sensing inputs on diverse objects in a physical simulator. By training with large-scale data in simulation, it enables the policy to generalize to unseen objects. However, leveraging simulation introduces the Sim2Real transfer problem. To mitigate this problem, we study different tactile representations and evaluate how each affects real-robot manipulation results after tr...
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