6 citations · 10 across the 12 of their papers we have counts for
15 papers
EqC: Equilibrium Energy Control for Introspective Lifelong Robot Learning
Haodong Yang, Runhan Huang, Bowen Zhang +7
Long-term robot autonomy depends on more than effective action generation: a policy must recognize when its behavior is no longer sufficiently supported and use assistance to impro…
WB-WAM: Heterogeneous Body-Hand Pre-training for Humanoid Loco-Manipulation
Chuan Qin, Shaoting Zhu, Siyuan Luo +4
Humanoid loco-manipulation demands coordinated body and hand behavior, while conventional robot pre-training data provide limited coverage of such whole-body motion. We present WB-…
G0.5: One Autoregressive Stream for Robot Reasoning and Action
Yicheng Liu, Zibin Dong, Baijun Ye +24
The prevailing recipe for Vision-Language-Action (VLA) models couples a pretrained VLM with a separately trained flow-matching action expert. This makes the VLM a context encoder r…
OMG: Omni-Modal Motion Generation for Generalist Humanoid Control
Siqiao Huang, Kun-Ying Lee, Dongming Qiao +5
Humanoid whole-body control has made significant progress in recent years, yet existing approaches remain limited to few-skill policies with heavy reward engineering, or motion tra…
Generative Control as Optimization: Time Unconditional Flow Matching for Adaptive and Robust Robotic Control
Zunzhe Zhang, Runhan Huang, Yicheng Liu +3
Diffusion models and flow matching have become a cornerstone of robotic imitation learning, yet they suffer from a structural inefficiency where inference is often bound to a fixed…
TTT-Parkour: Rapid Test-Time Training for Perceptive Robot Parkour
Shaoting Zhu, Baijun Ye, Jiaxuan Wang +5
Achieving highly dynamic parkour with humanoid robots on complex terrains unseen during the pre-training stage remains a challenge in robotics. Although general locomotion policies…
Hiking in the Wild: A Scalable Perceptive Parkour Framework for Humanoids
Shaoting Zhu, Ziwen Zhuang, Mengjie Zhao +2
Achieving robust humanoid locomotion in complex, unstructured environments requires transitioning from reactive proprioception to proactive perception. However, integrating exteroc…
Deep Whole-body Parkour
Ziwen Zhuang, Shaoting Zhu, Mengjie Zhao +1
Current approaches to humanoid control generally fall into two paradigms: perceptive locomotion, which handles terrain well but is limited to pedal gaits, and general motion tracki…
GS-Occ3D: Scaling Vision-only Occupancy Reconstruction with Gaussian Splatting
Baijun Ye, Minghui Qin, Saining Zhang +7
Occupancy is crucial for autonomous driving, providing essential geometric priors for perception and planning. However, existing methods predominantly rely on LiDAR-based occupancy…
RoboEngine: Plug-and-Play Robot Data Augmentation with Semantic Robot Segmentation and Background Generation
Chengbo Yuan, Suraj Joshi, Shaoting Zhu +3
Visual augmentation has become a crucial technique for enhancing the visual robustness of imitation learning. However, existing methods are often limited by prerequisites such as c…
MoE-Loco: Mixture of Experts for Multitask Locomotion
Runhan Huang, Shaoting Zhu, Yilun Du +1
We present MoE-Loco, a Mixture of Experts (MoE) framework for multitask locomotion for legged robots. Our method enables a single policy to handle diverse terrains, including bars,…
VR-Robo: A Real-to-Sim-to-Real Framework for Visual Robot Navigation and Locomotion
Shaoting Zhu, Linzhan Mou, Derun Li +3
Recent success in legged robot locomotion is attributed to the integration of reinforcement learning and physical simulators. However, these policies often encounter challenges whe…
Robust Robot Walker: Learning Agile Locomotion over Tiny Traps
Shaoting Zhu, Runhan Huang, Linzhan Mou +1
Quadruped robots must exhibit robust walking capabilities in practical applications. In this work, we propose a novel approach that enables quadruped robots to pass various small o…
SARO: Space-Aware Robot System for Terrain Crossing via Vision-Language Model
Shaoting Zhu, Derun Li, Linzhan Mou +3
The application of vision-language models (VLMs) has achieved impressive success in various robotics tasks. However, there are few explorations for these foundation models used in…
Multimodal-driven Talking Face Generation via a Unified Diffusion-based Generator
Chao Xu, Shaoting Zhu, Junwei Zhu +4
Multimodal-driven talking face generation refers to animating a portrait with the given pose, expression, and gaze transferred from the driving image and video, or estimated from t…