25 citations · 59 across the 31 of their papers we have counts for
11 papers · 1 filter
GarmentLab: A Unified Simulation and Benchmark for Garment Manipulation
Haoran Lu, Ruihai Wu, Yitong Li +7
Manipulating garments and fabrics has long been a critical endeavor in the development of home-assistant robots. However, due to complex dynamics and topological structures, garmen…
ManipGPT: Is Affordance Segmentation by Large Vision Models Enough for Articulated Object Manipulation?
Taewhan Kim, Hojin Bae, Zeming Li +4
Visual actionable affordance has emerged as a transformative approach in robotics, focusing on perceiving interaction areas prior to manipulation. Traditional methods rely on pixel…
ET-SEED: Efficient Trajectory-Level SE(3) Equivariant Diffusion Policy
Chenrui Tie, Yue Chen, Ruihai Wu +4
Imitation learning, e.g., diffusion policy, has been proven effective in various robotic manipulation tasks. However, extensive demonstrations are required for policy robustness an…
EqvAfford: SE(3) Equivariance for Point-Level Affordance Learning
Yue Chen, Chenrui Tie, Ruihai Wu +1
Humans perceive and interact with the world with the awareness of equivariance, facilitating us in manipulating different objects in diverse poses. For robotic manipulation, such e…
Broadcasting Support Relations Recursively from Local Dynamics for Object Retrieval in Clutters
Yitong Li, Ruihai Wu, Haoran Lu +4
In our daily life, cluttered objects are everywhere, from scattered stationery and books cluttering the table to bowls and plates filling the kitchen sink. Retrieving a target obje…
UniGarmentManip: A Unified Framework for Category-Level Garment Manipulation via Dense Visual Correspondence
Ruihai Wu, Haoran Lu, Yiyan Wang +2
Garment manipulation (e.g., unfolding, folding and hanging clothes) is essential for future robots to accomplish home-assistant tasks, while highly challenging due to the diversity…
PreAfford: Universal Affordance-Based Pre-Grasping for Diverse Objects and Environments
Kairui Ding, Boyuan Chen, Ruihai Wu +8
Robotic manipulation with two-finger grippers is challenged by objects lacking distinct graspable features. Traditional pre-grasping methods, which typically involve repositioning…
NaturalVLM: Leveraging Fine-grained Natural Language for Affordance-Guided Visual Manipulation
Ran Xu, Yan Shen, Xiaoqi Li +2
Enabling home-assistant robots to perceive and manipulate a diverse range of 3D objects based on human language instructions is a pivotal challenge. Prior research has predominantl…
UniDoorManip: Learning Universal Door Manipulation Policy Over Large-scale and Diverse Door Manipulation Environments
Yu Li, Xiaojie Zhang, Ruihai Wu +4
Learning a universal manipulation policy encompassing doors with diverse categories, geometries and mechanisms, is crucial for future embodied agents to effectively work in complex…
Articulated Object Manipulation with Coarse-to-fine Affordance for Mitigating the Effect of Point Cloud Noise
Suhan Ling, Yian Wang, Shiguang Wu +5
3D articulated objects are inherently challenging for manipulation due to the varied geometries and intricate functionalities associated with articulated objects.Point-level afford…
RoboEXP: Action-Conditioned Scene Graph via Interactive Exploration for Robotic Manipulation
Hanxiao Jiang, Binghao Huang, Ruihai Wu +5
We introduce the novel task of interactive scene exploration, wherein robots autonomously explore environments and produce an action-conditioned scene graph (ACSG) that captures th…