55 citations · 232 across the 30 of their papers we have counts for
4 papers · 1 filter
GenSim: Generating Robotic Simulation Tasks via Large Language Models
Lirui Wang, Yiyang Ling, Zhecheng Yuan +6
Collecting large amounts of real-world interaction data to train general robotic policies is often prohibitively expensive, thus motivating the use of simulation data. However, exi…
Abstract-to-Executable Trajectory Translation for One-Shot Task Generalization
Stone Tao, Xiaochen Li, Tongzhou Mu +3
Training long-horizon robotic policies in complex physical environments is essential for many applications, such as robotic manipulation. However, learning a policy that can genera…
DexMV: Imitation Learning for Dexterous Manipulation from Human Videos
Yuzhe Qin, Yueh-Hua Wu, Shaowei Liu +4
While significant progress has been made on understanding hand-object interactions in computer vision, it is still very challenging for robots to perform complex dexterous manipula…
Composing Task-Agnostic Policies with Deep Reinforcement Learning
Ahmed H. Qureshi, Jacob J. Johnson, Yuzhe Qin +3
The composition of elementary behaviors to solve challenging transfer learning problems is one of the key elements in building intelligent machines. To date, there has been plenty…