16 citations · 16 across the 5 of their papers we have counts for
5 papers
HAF: Adapting Generalist VLAs to Humanoid Whole-Body Loco-manipulation via Hierarchical Action Flow and Spectral Latent RL
Langzhe Gu, Chengkai Hou, Meng Li +14
Humanoid robots hold great promise as general-purpose agents in human-centered environments, yet generalist vision-language-action (VLA) foundation models are not readily applicabl…
HEX: Humanoid-Aligned Experts for Cross-Embodiment Whole-Body Manipulation
Shuanghao Bai, Meng Li, Xinyuan Lv +15
Humans achieve complex manipulation through coordinated whole-body control, whereas most Vision-Language-Action (VLA) models treat robot body parts largely independently, making hi…
RoboGene: Diversity-Driven Agentic Task Generation Framework for VLA Pre-training
Yixue Zhang, Kun Wu, Zhi Gao +12
The pursuit of general-purpose robotic manipulation is hindered by the scarcity of diverse, real-world interaction data. Unlike large-scale web vision-language data, robotic data c…
RoboMIND 2.0: A Multimodal, Bimanual Mobile Manipulation Dataset for Generalizable Embodied Intelligence
Chengkai Hou, Kun Wu, Jiaming Liu +30
While data-driven imitation learning has revolutionized robotic manipulation, current approaches remain constrained by the scarcity of large-scale, diverse real-world demonstration…
RoboMIND: Benchmark on Multi-embodiment Intelligence Normative Data for Robot Manipulation
Kun Wu, Chengkai Hou, Jiaming Liu +34
In this paper, we introduce RoboMIND (Multi-embodiment Intelligence Normative Data for Robot Manipulation), a dataset containing 107k demonstration trajectories across 479 diverse…