2 citations · 3 across the 11 of their papers we have counts for
15 papers
Gen2Dex: Learning Dexterous Manipulation from Simulation-Initialized Generated Video Demonstrations
Xiaowen Qiu, Yian Wang, Haoxiang You +1
Human video demonstrations provide rich manipulation strategies for dexterous manipulation learning. We study a setting in which a fully specified simulated scene is used to genera…
DexTaG: Tactile-as-Guidance in Reinforcement Learning for Dexterous Manipulation
Han Yang, Yian Wang, Yunlong Song +2
Glove-based motion capture is emerging as a scalable approach to collecting dexterous-hand demonstration data. However, due to the kinematic gap between the human and robot hand, t…
Self-Adaptive VLA for Robust Robot Deployment
Hongxin Zhang, Chunru Lin, Tsun-Hsuan Wang +2
While Vision-Language-Action (VLA) models demonstrate impressive capabilities in robotic manipulation, their memoryless nature renders them brittle to test-time environment shifts,…
IM-ENGINE: Image Editing for Embodied Data Generation
Yian Wang, Junyi Cao, Xiaowen Qiu +1
Learning-based manipulation requires supervision that is both semantically meaningful and physically executable, but current data pipelines often provide only one of these properti…
GS-Agent: Creating 4D Physical Worlds With Generative Simulation
Hongxin Zhang, Chunru Lin, Junyan Li +3
Creating dynamic and physically realistic 4D worlds from natural language descriptions is both fascinating and challenging. Traditional computer graphics methods rely on manual cre…
DLO-Lab: Benchmarking Deformable Linear Object Manipulations with Differentiable Physics
Junyi Cao, Yian Wang, Ziyan Xiong +3
We address the challenge of enabling robots to manipulate deformable linear objects (DLOs), such as ropes, cables, and rubber bands. Prior work has primarily focused on narrow, tas…
RoboWits: Unexpected Challenges for Robotic Creative Problem Solving
Chunru Lin, Hongxin Zhang, Fenghao Yu +5
The ability to reason, adapt, and creatively solve problems under unexpected challenges is essential for robots operating in real-world environments. However, current robotic bench…
PhyScensis: Physics-Augmented LLM Agents for Complex Physical Scene Arrangement
Yian Wang, Han Yang, Minghao Guo +5
Automatically generating interactive 3D environments is crucial for scaling up robotic data collection in simulation. While prior work has primarily focused on 3D asset placement,…
RobotSmith: Generative Robotic Tool Design for Acquisition of Complex Manipulation Skills
Chunru Lin, Haotian Yuan, Yian Wang +7
Endowing robots with tool design abilities is critical for enabling them to solve complex manipulation tasks that would otherwise be intractable. While recent generative frameworks…
MatchMaker: Automated Asset Generation for Robotic Assembly
Yian Wang, Bingjie Tang, Chuang Gan +4
Robotic assembly remains a significant challenge due to complexities in visual perception, functional grasping, contact-rich manipulation, and performing high-precision tasks. Simu…
Articulate AnyMesh: Open-Vocabulary 3D Articulated Objects Modeling
Xiaowen Qiu, Jincheng Yang, Yian Wang +5
3D articulated objects modeling has long been a challenging problem, since it requires to capture both accurate surface geometries and semantically meaningful and spatially precise…
UBSoft: A Simulation Platform for Robotic Skill Learning in Unbounded Soft Environments
Chunru Lin, Jugang Fan, Yian Wang +6
It is desired to equip robots with the capability of interacting with various soft materials as they are ubiquitous in the real world. While physics simulations are one of the pred…
Architect: Generating Vivid and Interactive 3D Scenes with Hierarchical 2D Inpainting
Yian Wang, Xiaowen Qiu, Jiageng Liu +6
Creating large-scale interactive 3D environments is essential for the development of Robotics and Embodied AI research. Current methods, including manual design, procedural generat…
Thin-Shell Object Manipulations With Differentiable Physics Simulations
Yian Wang, Juntian Zheng, Zhehuan Chen +4
In this work, we aim to teach robots to manipulate various thin-shell materials. Prior works studying thin-shell object manipulation mostly rely on heuristic policies or learn poli…
DIFFTACTILE: A Physics-based Differentiable Tactile Simulator for Contact-rich Robotic Manipulation
Zilin Si, Gu Zhang, Qingwei Ben +4
We introduce DIFFTACTILE, a physics-based differentiable tactile simulation system designed to enhance robotic manipulation with dense and physically accurate tactile feedback. In…