30 citations · 31 across the 4 of their papers we have counts for
4 papers
TacPalm: A Soft Gripper with a Biomimetic Optical Tactile Palm for Stable Precise Grasping
Xuyang Zhang, Tianqi Yang, Dandan Zhang +1
Manipulating fragile objects in environments such as homes and factories requires stable and gentle grasping along with precise and safe placement. Compared to traditional rigid gr…
Attention for Robot Touch: Tactile Saliency Prediction for Robust Sim-to-Real Tactile Control
Yijiong Lin, Mauro Comi, Alex Church +2
High-resolution tactile sensing can provide accurate information about local contact in contact-rich robotic tasks. However, the deployment of such tasks in unstructured environmen…
Sim-to-Real Model-Based and Model-Free Deep Reinforcement Learning for Tactile Pushing
Max Yang, Yijiong Lin, Alex Church +4
Object pushing presents a key non-prehensile manipulation problem that is illustrative of more complex robotic manipulation tasks. While deep reinforcement learning (RL) methods ha…
Bi-Touch: Bimanual Tactile Manipulation with Sim-to-Real Deep Reinforcement Learning
Yijiong Lin, Alex Church, Max Yang +4
Bimanual manipulation with tactile feedback will be key to human-level robot dexterity. However, this topic is less explored than single-arm settings, partly due to the availabilit…