5 papers
HarmoWAM: Harmonizing Generalizable and Precise Manipulation via Adaptive World Action Models
Qiuxuan Feng, Jiale Yu, Jiaming Liu +8
World Action Models (WAMs) have emerged as a promising paradigm for robot control by modeling physical dynamics. Current WAMs generally follow two paradigms: the "Imagine-then-Exec…
Look Before Acting: Enhancing Vision Foundation Representations for Vision-Language-Action Models
Yulin Luo, Hao Chen, Zhuangzhe Wu +10
Vision-Language-Action (VLA) models have recently emerged as a promising paradigm for robotic manipulation, in which reliable action prediction critically depends on accurately int…
URDF-Anything+: End-to-End Generation for Simulation-Ready Articulated Assets
Zhuangzhe Wu, Yue Xin, Chengkai Hou +4
Articulated objects are fundamental for robotics, simulation of physics, and interactive virtual environments. However, recovering them from visual observations is inherently chall…
URDF-Anything: Constructing Articulated Objects with 3D Multimodal Language Model
Zhe Li, Xiang Bai, Jieyu Zhang +5
Constructing accurate digital twins of articulated objects is essential for robotic simulation training and embodied AI world model building, yet historically requires painstaking…
EMD: Explicit Motion Modeling for High-Quality Street Gaussian Splatting
Xiaobao Wei, Qingpo Wuwu, Zhongyu Zhao +5
Photorealistic reconstruction of street scenes is essential for developing real-world simulators in autonomous driving. While recent methods based on 3D/4D Gaussian Splatting (GS)…