activity
20192023
most citedRearrangement: A Challenge for Embodied AI

101 citations · 405 across the 23 of their papers we have counts for

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13 papers · 1 filter

cs.RO2023★ 1 cited

AnyTeleop: A General Vision-Based Dexterous Robot Arm-Hand Teleoperation System

Yuzhe Qin, Wei Yang, Binghao Huang +5

Vision-based teleoperation offers the possibility to endow robots with human-level intelligence to physically interact with the environment, while only requiring low-cost camera se…

cs.RO2023★ 21 cited

EasyHeC: Accurate and Automatic Hand-eye Calibration via Differentiable Rendering and Space Exploration

Linghao Chen, Yuzhe Qin, Xiaowei Zhou +1

Hand-eye calibration is a critical task in robotics, as it directly affects the efficacy of critical operations such as manipulation and grasping. Traditional methods for achieving…

cs.RO2023★ 22 cited

ManiSkill2: A Unified Benchmark for Generalizable Manipulation Skills

Jiayuan Gu, Fanbo Xiang, Xuanlin Li +12

Generalizable manipulation skills, which can be composed to tackle long-horizon and complex daily chores, are one of the cornerstones of Embodied AI. However, existing benchmarks,…

cs.RO2022★ 12 cited

DexPoint: Generalizable Point Cloud Reinforcement Learning for Sim-to-Real Dexterous Manipulation

Yuzhe Qin, Binghao Huang, Zhao-Heng Yin +2

We propose a sim-to-real framework for dexterous manipulation which can generalize to new objects of the same category in the real world. The key of our framework is to train the m…

cs.RO2022★ 8 cited

Frame Mining: a Free Lunch for Learning Robotic Manipulation from 3D Point Clouds

Minghua Liu, Xuanlin Li, Zhan Ling +2

We study how choices of input point cloud coordinate frames impact learning of manipulation skills from 3D point clouds. There exist a variety of coordinate frame choices to normal…

cs.RO2022

A Real2Sim2Real Method for Robust Object Grasping with Neural Surface Reconstruction

Luobin Wang, Runlin Guo, Quan Vuong +3

Recent 3D-based manipulation methods either directly predict the grasp pose using 3D neural networks, or solve the grasp pose using similar objects retrieved from shape databases.…

cs.RO2022★ 10 cited

Multi-skill Mobile Manipulation for Object Rearrangement

Jiayuan Gu, Devendra Singh Chaplot, Hao Su +1

We study a modular approach to tackle long-horizon mobile manipulation tasks for object rearrangement, which decomposes a full task into a sequence of subtasks. To tackle the entir…

cs.RO2022★ 4 cited

Contact Points Discovery for Soft-Body Manipulations with Differentiable Physics

Sizhe Li, Zhiao Huang, Tao Du +3

Differentiable physics has recently been shown as a powerful tool for solving soft-body manipulation tasks. However, the differentiable physics solver often gets stuck when the ini…

cs.RO2022★ 1 cited

From One Hand to Multiple Hands: Imitation Learning for Dexterous Manipulation from Single-Camera Teleoperation

Yuzhe Qin, Hao Su, Xiaolong Wang

We propose to perform imitation learning for dexterous manipulation with multi-finger robot hand from human demonstrations, and transfer the policy to the real robot hand. We intro…

cs.RO2022★ 2 cited

Close the Optical Sensing Domain Gap by Physics-Grounded Active Stereo Sensor Simulation

Xiaoshuai Zhang, Rui Chen, Ang Li +11

In this paper, we focus on the simulation of active stereovision depth sensors, which are popular in both academic and industry communities. Inspired by the underlying mechanism of…

cs.RO2021

Single RGB-D Camera Teleoperation for General Robotic Manipulation

Quan Vuong, Yuzhe Qin, Runlin Guo +3

We propose a teleoperation system that uses a single RGB-D camera as the human motion capture device. Our system can perform general manipulation tasks such as cloth folding, hamme…

cs.RO2021★ 6 cited

OCRTOC: A Cloud-Based Competition and Benchmark for Robotic Grasping and Manipulation

Ziyuan Liu, Wei Liu, Yuzhe Qin +8

In this paper, we propose a cloud-based benchmark for robotic grasping and manipulation, called the OCRTOC benchmark. The benchmark focuses on the object rearrangement problem, spe…

cs.RO2019★ 55 cited

S4G: Amodal Single-view Single-Shot SE(3) Grasp Detection in Cluttered Scenes

Yuzhe Qin, Rui Chen, Hao Zhu +3

Grasping is among the most fundamental and long-lasting problems in robotics study. This paper studies the problem of 6-DoF(degree of freedom) grasping by a parallel gripper in a c…