7 citations · 7 across the 7 of their papers we have counts for
5 papers · 1 filter
DockAnywhere: Data-Efficient Visuomotor Policy Learning for Mobile Manipulation via Novel Demonstration Generation
Ziyu Shan, Yuheng Zhou, Gaoyuan Wu +3
Mobile manipulation is a fundamental capability that enables robots to interact in expansive environments such as homes and factories. Most existing approaches follow a two-stage p…
RoCo Challenge at AAAI 2026: Benchmarking Robotic Collaborative Manipulation for Assembly Towards Industrial Automation
Haichao Liu, Yuheng Zhou, Zhenyu Wu +14
Embodied Artificial Intelligence (EAI) is rapidly developing, gradually subverting previous autonomous systems' paradigms from isolated perception to integrated, continuous action.…
UniManip: Open-World Robotic Manipulation via Agentic Operational Graphs
Haichao Liu, Yuanjiang Xue, Yuheng Zhou +5
Achieving general-purpose robotic manipulation requires robots to bridge high-level semantic intent with low-level physical interaction in unstructured environments. However, zero-…
VLA-RL: Towards Masterful and General Robotic Manipulation with Scalable Reinforcement Learning
Guanxing Lu, Wenkai Guo, Chubin Zhang +5
Recent high-capacity vision-language-action (VLA) models have demonstrated impressive performance on a range of robotic manipulation tasks by imitating human demonstrations. Howeve…
MoManipVLA: Transferring Vision-language-action Models for General Mobile Manipulation
Zhenyu Wu, Yuheng Zhou, Xiuwei Xu +2
Mobile manipulation is the fundamental challenge for robotics to assist humans with diverse tasks and environments in everyday life. However, conventional mobile manipulation appro…