3 papers
cs.RO2025
In-N-On: Scaling Egocentric Manipulation with in-the-wild and on-task Data
Xiongyi Cai, Ri-Zhao Qiu, Geng Chen +5
Egocentric videos are a valuable and scalable data source to learn manipulation policies. However, due to significant data heterogeneity, most existing approaches utilize human dat…
cs.RO2025
HMC: Learning Heterogeneous Meta-Control for Contact-Rich Loco-Manipulation
Lai Wei, Xuanbin Peng, Ri-Zhao Qiu +3
Learning from real-world robot demonstrations holds promise for interacting with complex real-world environments. However, the complexity and variability of interaction dynamics of…
cs.RO2025
AMO: Adaptive Motion Optimization for Hyper-Dexterous Humanoid Whole-Body Control
Jialong Li, Xuxin Cheng, Tianshu Huang +3
Humanoid robots derive much of their dexterity from hyper-dexterous whole-body movements, enabling tasks that require a large operational workspace: such as picking objects off the…