1 citations · 2 across the 9 of their papers we have counts for
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RobustVLA: On Robustness of Vision-Language-Action Model against Multi-Modal Perturbations
Jianing Guo, Zhenhong Wu, Chang Tu +13
In Vision-Language-Actionf(VLA) models, robustness to real-world perturbations is critical for deployment. Existing methods target simple visual disturbances, overlooking the broad…
Learning to Ball: Composing Policies for Long-Horizon Basketball Moves
Pei Xu, Zhen Wu, Ruocheng Wang +5
Learning a control policy for a multi-phase, long-horizon task, such as basketball maneuvers, remains challenging for reinforcement learning approaches due to the need for seamless…
OmniRetarget: Interaction-Preserving Data Generation for Humanoid Whole-Body Loco-Manipulation and Scene Interaction
Lujie Yang, Xiaoyu Huang, Zhen Wu +6
A dominant paradigm for teaching humanoid robots complex skills is to retarget human motions as kinematic references to train reinforcement learning (RL) policies. However, existin…
Zero-Shot Human-Object Interaction Synthesis with Multimodal Priors
Yuke Lou, Yiming Wang, Zhen Wu +4
Human-object interaction (HOI) synthesis is important for various applications, ranging from virtual reality to robotics. However, acquiring 3D HOI data is challenging due to its c…
MTGS: Multi-Traversal Gaussian Splatting
Tianyu Li, Yihang Qiu, Zhenhua Wu +4
Multi-traversal data, commonly collected through daily commutes or by self-driving fleets, provides multiple viewpoints for scene reconstruction within a road block. This data offe…
STRIDE: Automating Reward Design, Deep Reinforcement Learning Training and Feedback Optimization in Humanoid Robotics Locomotion
Zhenwei Wu, Jinxiong Lu, Yuxiao Chen +3
Humanoid robotics presents significant challenges in artificial intelligence, requiring precise coordination and control of high-degree-of-freedom systems. Designing effective rewa…