7 papers
TACO: TActile World Model as a Self-COrrector for Scalable Robot Policy Post-Training
Shengbang Liu, Yueru Jia, Yuyang Yan +7
Vision-Language-Action models and World Action Models have shown promising generalization in robotic manipulation but remain fragile in contact-rich tasks, where contact perturbati…
HarmoWAM: Harmonizing Generalizable and Precise Manipulation via Adaptive World Action Models
Qiuxuan Feng, Jiale Yu, Jiaming Liu +8
World Action Models (WAMs) have emerged as a promising paradigm for robot control by modeling physical dynamics. Current WAMs generally follow two paradigms: the "Imagine-then-Exec…
RoboGene: Boosting VLA Pre-training via Diversity-Driven Agentic Framework for Real-World Task Generation
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 data collection from web in vision or language, robo…
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…
EmpathyAgent: Can Embodied Agents Conduct Empathetic Actions?
Xinyan Chen, Jiaxin Ge, Hongming Dai +6
Empathy is fundamental to human interactions, yet it remains unclear whether embodied agents can provide human-like empathetic support. Existing works have studied agents' tasks so…
CordViP: Correspondence-based Visuomotor Policy for Dexterous Manipulation in Real-World
Yankai Fu, Qiuxuan Feng, Ning Chen +8
Achieving human-level dexterity in robots is a key objective in the field of robotic manipulation. Recent advancements in 3D-based imitation learning have shown promising results,…