activity
20232026
most citedWhere2Explore: Few-shot Affordance Learning for Unseen Novel Categories of Articulated Objects

6 citations · 15 across the 20 of their papers we have counts for

collaborators
Showing 2024Show all

7 papers · 1 filter

cs.RO2024

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…

cs.RO2024★ 1 cited

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…

cs.RO2024★ 1 cited

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…

cs.RO2024

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…

cs.RO2024

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…

cs.CV2024

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…

cs.RO2024★ 1 cited

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…