3 papers
cs.RO2025
MimicDroid: In-Context Learning for Humanoid Robot Manipulation from Human Play Videos
Rutav Shah, Shuijing Liu, Qi Wang +5
We aim to enable humanoid robots to efficiently solve new manipulation tasks from a few video examples. In-context learning (ICL) is a promising framework for achieving this goal d…
cs.RO2025
Sim-and-Real Co-Training: A Simple Recipe for Vision-Based Robotic Manipulation
Abhiram Maddukuri, Zhenyu Jiang, Lawrence Yunliang Chen +12
Large real-world robot datasets hold great potential to train generalist robot models, but scaling real-world human data collection is time-consuming and resource-intensive. Simula…
cs.RO2024
KinScene: Model-Based Mobile Manipulation of Articulated Scenes
Cheng-Chun Hsu, Ben Abbatematteo, Zhenyu Jiang +3
Sequentially interacting with articulated objects is crucial for a mobile manipulator to operate effectively in everyday environments. To enable long-horizon tasks involving articu…