activity
20222024
most citedTowards Precise Model-free Robotic Grasping with Sim-to-Real Transfer Learning

6 citations · 9 across the 9 of their papers we have counts for

collaborators

9 papers

cs.LG2024

Subequivariant Reinforcement Learning in 3D Multi-Entity Physical Environments

Runfa Chen, Ling Wang, Yu Du +4

Learning policies for multi-entity systems in 3D environments is far more complicated against single-entity scenarios, due to the exponential expansion of the global state space as…

cs.CV2024

Close the Sim2real Gap via Physically-based Structured Light Synthetic Data Simulation

Kaixin Bai, Lei Zhang, Zhaopeng Chen +2

Despite the substantial progress in deep learning, its adoption in industrial robotics projects remains limited, primarily due to challenges in data acquisition and labeling. Previ…

cs.CV2024

Equivariant Local Reference Frames for Unsupervised Non-rigid Point Cloud Shape Correspondence

Ling Wang, Runfa Chen, Yikai Wang +6

Unsupervised non-rigid point cloud shape correspondence underpins a multitude of 3D vision tasks, yet itself is non-trivial given the exponential complexity stemming from inter-poi…

cs.RO2024

A Collision-Aware Cable Grasping Method in Cluttered Environment

Lei Zhang, Kaixin Bai, Qiang Li +2

We introduce a Cable Grasping-Convolutional Neural Network designed to facilitate robust cable grasping in cluttered environments. Utilizing physics simulations, we generate an ext…

cs.RO2023

PoseFusion: Robust Object-in-Hand Pose Estimation with SelectLSTM

Yuyang Tu, Junnan Jiang, Shuang Li +3

Accurate estimation of the relative pose between an object and a robot hand is critical for many manipulation tasks. However, most of the existing object-in-hand pose datasets use…

cs.RO20231 cited

Reinforcement Learning Based Pushing and Grasping Objects from Ungraspable Poses

Hao Zhang, Hongzhuo Liang, Lin Cong +4

Grasping an object when it is in an ungraspable pose is a challenging task, such as books or other large flat objects placed horizontally on a table. Inspired by human manipulation…