99 citations · 100 across the 6 of their papers we have counts for
4 papers · 1 filter
DexNinja: Learning Robust Dexterous Cutting Policy with a Real-to-Sim-to-Real Data Engine
Haozhe Lou, Runyi Yang, Wanqi Zhong +10
Cutting a piece of food looks effortless in human hands. For a robot, however, every cut is a high-contact interaction with a deformable, elasto-plastic object whose behavior chang…
Echo in the Steps: Learning Perceptive Humanoid Parkour with Gated Memory
Ming-Ju Lee, Zizhuo Wang, Shaoting Zhu +3
While recent advances in perceptive locomotion have enabled humanoid robots to traverse structured terrains, agile parkour in highly discontinuous environments remains an open chal…
TactileStep: Sole Tactile Learning for Regulating Foot-Terrain Interaction in Humanoid Locomotion
Zizhuo Wang, Ming-ju Lee, Shaoting Zhu +3
Humanoid parkour policies can traverse various terrains, but task completion may mask challenges of harsh landings, edge contacts, and unstable stance contacts. Humans naturally re…
D-REX: Differentiable Real-to-Sim-to-Real Engine for Learning Dexterous Grasping
Haozhe Lou, Mingtong Zhang, Haoran Geng +9
Simulation provides a cost-effective and flexible platform for data generation and policy learning to develop robotic systems. However, bridging the gap between simulation and real…