2 citations · 2 across the 5 of their papers we have counts for
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Embodiment-Aware Generalist Specialist Distillation for Unified Humanoid Whole-Body Control
Quanquan Peng, Yunfeng Lin, Yufei Xue +2
Humanoid Whole-Body Controllers trained with reinforcement learning (RL) have recently achieved remarkable performance, yet many target a single robot embodiment. Variations in dyn…
UniCon: A Unified System for Efficient Robot Learning Transfers
Yunfeng Lin, Li Xu, Yong Yu +2
Deploying learning-based controllers across heterogeneous robots is challenging due to platform differences, inconsistent interfaces, and inefficient middleware. To address these i…
H-Zero: Cross-Humanoid Locomotion Pretraining Enables Few-shot Novel Embodiment Transfer
Yunfeng Lin, Minghuan Liu, Yufei Xue +4
The rapid advancement of humanoid robotics has intensified the need for robust and adaptable controllers to enable stable and efficient locomotion across diverse platforms. However…
Manipulation as in Simulation: Enabling Accurate Geometry Perception in Robots
Minghuan Liu, Zhengbang Zhu, Xiaoshen Han +12
Modern robotic manipulation primarily relies on visual observations in a 2D color space for skill learning but suffers from poor generalization. In contrast, humans, living in a 3D…
D4W: Dependable Data-Driven Dynamics for Wheeled Robots
Yunfeng Lin, Minghuan Liu, Yong Yu
Wheeled robots have gained significant attention due to their wide range of applications in manufacturing, logistics, and service industries. However, due to the difficulty of buil…
GenSim2: Scaling Robot Data Generation with Multi-modal and Reasoning LLMs
Pu Hua, Minghuan Liu, Annabella Macaluso +4
Robotic simulation today remains challenging to scale up due to the human efforts required to create diverse simulation tasks and scenes. Simulation-trained policies also face scal…