Xiaohan Zhang

I am currently a robotics researcher at Boston Dynamics AI Institute. I completed my PhD in Computer Science at the State University of New York at Binghamton, advised by Shiqi Zhang. In the summer and fall of 2023, I was a Research Scientist Intern in the Embodied AI team at Meta AI (FAIR) working with Chris Paxton. In the spring of 2023, I spent time visiting the Learning Agents Research Group (LARG) at the University of Texas at Austin, supervised by Peter Stone. In the summer of 2022, I was a Student Researcher with the Robotics team at Google DeepMind. I obtained my bachelor's degree from Renmin University of China in 2019.

                              

Publications

DKPROMPT: Domain Knowledge Prompting Vision-Language Models for Open-World Planning

Xiaohan Zhang, Zainab Altaweel*, Yohei Hayamizu*, Yan Ding, Saeid Amiri, Hao Yang, Andy Kaminski, Chad Esselink, and Shiqi Zhang (*Equal Contribution)

CVPR EAI Workshop, 2024

OpenEQA: Embodied Question Answering in the Era of Foundation Models

Arjun Majumdar*, Anurag Ajay*, Xiaohan Zhang*, et al. (*Equal Contribution)

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024

SLAP: Spatial-Language Attention Policies

Priyam Parashar, Vidhi Jain, Xiaohan Zhang, Jay Vakil, Sam Powers, Yonatan Bisk, and Chris Paxton

Conference on Robot Learning (CoRL), 2023

Symbolic State Space Optimization for Long Horizon Mobile Manipulation Planning

Xiaohan Zhang, Yifeng Zhu, Yan Ding, Yuqian Jiang, Yuke Zhu, Peter Stone, and Shiqi Zhang

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2023

Task and Motion Planning with Large Language Models for Object Rearrangement

Yan Ding*, Xiaohan Zhang*, Chris Paxton, and Shiqi Zhang (*Equal Contribution)

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2023

Integrating Action Knowledge and LLMs for Task Planning and Situation Handling in Open Worlds

Yan Ding, Xiaohan Zhang, Saeid Amiri, Nieqing Cao, Hao Yang, Andy Kaminski, Chad Esselink, and Shiqi Zhang

Autonomous Robots, 2023

LLM+P: Empowering Large Language Models with Optimal Planning Proficiency

Bo Liu*, Yuqian Jiang*, Xiaohan Zhang, Qiang Liu, Shiqi Zhang, Joydeep Biswas, and Peter Stone (*Equal Contribution)

ArXiv, 2023

Multimodal Embodied Attribute Learning by Robots for Object-Centric Action Policies

Xiaohan Zhang, Saeid Amiri, Jivko Sinapov, Jesse Thomason, Peter Stone, and Shiqi Zhang

Autonomous Robots, 2023

Robotic Table Wiping via Reinforcement Learning and Whole-body Trajectory Optimization

Thomas Lew, Sumeet Singh, Mario Prats, Jeffrey Bingham, Jonathan Weisz, Benjie Holson, Xiaohan Zhang, Vikas Sindhwani, Yao Lu, Fei Xia, Peng Xu, Tingnan Zhang, Jie Tan, and Montserrat Gonzalez

IEEE International Conference on Robotics and Automation (ICRA), 2023

Learning to Ground Objects for Robot Task and Motion Planning

Yan Ding, Xiaohan Zhang, Xingyue Zhan, and Shiqi Zhang

IEEE Robotics and Automation Letters (RA-L), 2022

Visually Grounded Task and Motion Planning for Mobile Manipulation

Xiaohan Zhang, Yifeng Zhu, Yan Ding, Yuke Zhu, Peter Stone, and Shiqi Zhang

IEEE International Conference on Robotics and Automation (ICRA), 2022

Learning to Guide Human Attention on Mobile Telepresence Robots with 360 Vision

Kishan Chandan, Jack Albertson, Xiaohan Zhang, Xiaoyang Zhang, Yao Liu, and Shiqi Zhang

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021

Planning Multimodal Exploratory Actions for Online Robot Attribute Learning

Xiaohan Zhang, Jivko Sinapov, and Shiqi Zhang

Robotics: Science and Systems (RSS), 2021

Task-Motion Planning for Safe and Efficient Urban Driving

Yan Ding, Xiaohan Zhang, Xingyue Zhan, and Shiqi Zhang

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020