6 citations · 19 across the 13 of their papers we have counts for
4 papers · 1 filter
Learning Dexterous Manipulation with Quantized Hand State
Ying Feng, Hongjie Fang, Yinong He +5
Dexterous robotic hands enable robots to perform complex manipulations that require fine-grained control and adaptability. Achieving such manipulation is challenging because the hi…
History-Aware Visuomotor Policy Learning via Point Tracking
Jingjing Chen, Hongjie Fang, Chenxi Wang +2
Many manipulation tasks require memory beyond the current observation, yet most visuomotor policies rely on the Markov assumption and thus struggle with repeated states or long-hor…
AirExo-2: Scaling up Generalizable Robotic Imitation Learning with Low-Cost Exoskeletons
Hongjie Fang, Chenxi Wang, Yiming Wang +11
Scaling up robotic imitation learning for real-world applications requires efficient and scalable demonstration collection methods. While teleoperation is effective, it depends on…
AnyDexGrasp: General Dexterous Grasping for Different Hands with Human-level Learning Efficiency
Hao-Shu Fang, Hengxu Yan, Zhenyu Tang +3
We introduce an efficient approach for learning dexterous grasping with minimal data, advancing robotic manipulation capabilities across different robotic hands. Unlike traditional…