My research interests lie in 🤖robot learning ,🦾dexterous manipulation and 🤝Human-Robot Perception Alignment.
My long-term goal is to create true robotic life, pushing the boundaries of what’s possible with machines. I’m open to collaborations on robotics-related projects! Whether you’re a researcher looking for a partner , feel free to reach out to me👋 @
Schedule time with me
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DexSinGrasp: Learning a Unified Policy for Dexterous Object Singulation and Grasping in Cluttered Environments
Lixin Xu, Zixuan Liu, Zhewei Gui, Jingxiang Guo, Zeyu Jiang, Zhixuan Xu, Chongkai Gao, Lin Shao
In submission to IROS Website
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arXiv
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Code
Manual2Skill: Learning to Read Manuals and Acquire Robotic Skills for Furniture Assembly Using Vision-Language Models
Chenrui Tie, Shengxiang Sun, Jinxuan Zhu, Yiwei Liu, Jingxiang Guo, Yue Hu, Haonan Chen, Junting Chen, Ruihai Wu, Lin Shao
In submission Website
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arxiv
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Code
MetaFold: A Closed-loop Pipeline for Universal Clothing Folding via End-to-end Point Cloud Trajectory Generation
Haonan Chen, Junxiao Li, Chongkai Gao, Zhixuan Xu, Chenting Wang, Yiwen Hou, Jingxiang Guo, Shensi Xu, Jiaqi Huang, Weidong Wang, Lin Shao
In submission to IROS Website
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arxiv
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Code
TelePreview: A User-Friendly Teleoperation System with Virtual Arm Assistance for Enhanced Effectiveness
Jingxiang Guo*,
Jiayu Luo*,
Zhenyu Wei*,
Yiwen Hou,
Zhixuan Xu,
Xiaoyi Lin,
Chongkai Gao,
Lin Shao Website
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arXiv
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Code (Coming soon)
In submission
TL;DR:
Implement a low-cost teleoperation system utilizing data gloves and IMU sensors, paired with an assistant
module that improves data collection process by visualizing future robot operations through visual previews.
$\mathcal{D(R,O)}$ Grasp: A Unified Representation of Robot and Object Interaction for Cross-Embodiment Dexterous Grasping
Zhenyu Wei*,
Zhixuan Xu*,
Jingxiang Guo,
Yiwen Hou,
Chongkai Gao,
Zhehao Cai,
Jiayu Luo,
Lin Shao Website
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arXiv
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Code
TL;DR:
Introduce $\mathcal{D(R,O)}$, a novel interaction-centric representation for dexterous grasping tasks that
goes beyond traditional robot-centric and object-centric approaches, enabling robust generalization across
diverse robotic hands and objects.
MASQ: Multi-Agent Reinforcement Learning for Single Quadruped Robot Locomotion
Qi Liu*,
Jingxiang Guo*,
Sixu Lin,
Shuaikang Ma,
Jinxuan Zhu,
Yanjie Li
In submission arXiv
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Video
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Press
TL;DR:
Introduce MASQ, a novel approach using multi-agent reinforcement learning (MARL) for single quadruped robot locomotion. By treating each leg as an independent agent, MASQ accelerates learning and boosts real-world robustness, surpassing traditional methods.
Multi-Agent Target Assignment and Path Finding for Intelligent Warehouse: A Cooperative Multi-Agent Deep Reinforcement Learning Perspective
Qi Liu, Jianqi Gao, Dongjie Zhu, Zhongjian Qiao, Jingxiang Guo, Pengbin Chen, Yanjie Li
In submission to IROS arXiv
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Code
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Press
Logarithmic Function Matters Policy Gradient Deep Reinforcement Learning
Qi Liu, Jingxiang Guo, Zhongjian Qiao, Pengbin Chen, Yanjie Li
⭐️ Accepted in DAI 2024 (Oral) ⭐️
arXiv
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Code
Momentum Prediction for Tennis Matches Based on Counter-Factual Analysis and Multi-LGBM
Jingxiang Guo, Jinxuan Zhu, Sixu Lin, Feng Shi
IEEE Xpolre
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Code
ECAPA-TDNN Embeddings for Speaker Recognition
Jingxiang Guo, Jinxuan Zhu, Sixu Lin, Feng Shi
IEEE Xpolre
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Code