6 citations · 6 across the 7 of their papers we have counts for
8 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…
SkillX: Unified Multi-Skill Policy Learning for Humanoid Soccer
Zhangchen Ye, Enxuan Ruan, Yifei Bao +10
Humanoid soccer is a challenging testbed for dynamic whole-body control, requiring robots to coordinate balance, locomotion, object interaction, and skill switching over long horiz…
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…
Flexible Locomotion Learning with Diffusion Model Predictive Control
Runhan Huang, Haldun Balim, Heng Yang +1
Legged locomotion demands controllers that are both robust and adaptable, while remaining compatible with task and safety considerations. However, model-free reinforcement learning…
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…