1 citations · 1 across the 6 of their papers we have counts for
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SSR: Scaling Surefooted and Symmetric Humanoid Traversal to the Open World
Ruiqi Yu, Yiwen Wang, Yuan Hao +2
Extending humanoid traversal to the open world is key to practical deployment in human environments, but remains challenging. The robot must use vision to ensure safe and reliable…
CReF: Cross-modal and Recurrent Fusion for Depth-conditioned Humanoid Locomotion
Yuan Hao, Ruiqi Yu, Shixin Luo +3
Stable traversal over geometrically complex terrain increasingly requires exteroceptive perception, yet prior perceptive humanoid locomotion methods often remain tied to explicit g…
START: Traversing Sparse Footholds with Terrain Reconstruction
Ruiqi Yu, Qianshi Wang, Hongyi Li +4
Traversing terrains with sparse footholds like legged animals presents a promising yet challenging task for quadruped robots, as it requires precise environmental perception and ag…
KiVi: Kinesthetic-Visuospatial Integration for Dynamic and Safe Egocentric Legged Locomotion
Peizhuo Li, Hongyi Li, Yuxuan Ma +8
Vision-based locomotion has shown great promise in enabling legged robots to perceive and adapt to complex environments. However, visual information is inherently fragile, being vu…
PIE: Parkour with Implicit-Explicit Learning Framework for Legged Robots
Shixin Luo, Songbo Li, Ruiqi Yu +3
Parkour presents a highly challenging task for legged robots, requiring them to traverse various terrains with agile and smooth locomotion. This necessitates comprehensive understa…
Walking with Terrain Reconstruction: Learning to Traverse Risky Sparse Footholds
Ruiqi Yu, Qianshi Wang, Yizhen Wang +3
Traversing risky terrains with sparse footholds presents significant challenges for legged robots, requiring precise foot placement in safe areas. To acquire comprehensive exteroce…
Toward Understanding Key Estimation in Learning Robust Humanoid Locomotion
Zhicheng Wang, Wandi Wei, Ruiqi Yu +2
Accurate state estimation plays a critical role in ensuring the robust control of humanoid robots, particularly in the context of learning-based control policies for legged robots.…