2 citations · 2 across the 12 of their papers we have counts for
7 papers · 2 filters
ForceWAM: Decoupling Future and Response Learning from Demo and Play Data for Contact-Rich Manipulation
Zijun Xu, Wendi Chen, Xinkai Wang +16
Expert demonstrations show how to complete contact-rich tasks, but provide limited coverage of how interaction forces respond to different actions. Task-agnostic play provides broa…
ΔWAM: Distilling Action Tangent Fields into World Action Models
Ke Wu, Hanwen Huang, Bo Gu +6
World Action Models (WAM) improve robot policies by augmenting sparse action supervision with dense future prediction. However, much of the predictable future is dominated by appea…
CAP: Continuously Adaptive Perception-Blind Humanoid Locomotion via Learned Denoising
Hongjin Chen, Zijun Xu, Shihao Ma +8
Humanoid locomotion across complex terrain demands forward-looking exteroception to anticipate obstacles, yet this signal is unreliable in real-world deployment, failing partially…
AutoSpeed: Annotation-Free Stage-Adaptive Motion Speed Learning for Robot Manipulation
Qingda Hu, Ziheng Qiu, Jieru Zhao +2
Different stages of manipulation tasks exhibit varying levels of difficulty, suggesting stage-dependent motion speeds and temporal prediction horizons. However, existing IL-based v…
Learning High-Frequency Continuous Action Chunks in Latent Space
Kunyun Wang, Yuhang Zheng, Yupeng Zheng +2
Modern robotic policies increasingly rely on action chunking to execute complex tasks in the physical world. While action chunking improves temporal consistency at moderate action…
Flash-Mono: Feed-Forward Accelerated Gaussian Splatting Monocular SLAM
Zicheng Zhang, Ke Wu, Xiangting Meng +3
Monocular 3D Gaussian Splatting SLAM suffers from critical limitations in time efficiency, geometric accuracy, and multi-view consistency. These issues stem from the time-consuming…
Rhythm: Learning Interactive Whole-Body Control for Dual Humanoids
Hongjin Chen, Wei Zhang, Pengfei Li +10
Realizing interactive whole-body control for multi-humanoid systems is critical for unlocking complex collaborative capabilities in shared environments. Although recent advancement…