Xiaohan Zhang

Orcid: 0000-0003-3505-8491

Affiliations:
  • State University of New York at Binghamton, NY, USA


According to our database1, Xiaohan Zhang authored at least 15 papers between 2020 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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In proceedings 
Article 
PhD thesis 
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Bibliography

2023
Integrating action knowledge and LLMs for task planning and situation handling in open worlds.
Auton. Robots, December, 2023

Multimodal embodied attribute learning by robots for object-centric action policies.
Auton. Robots, June, 2023

LLM+P: Empowering Large Language Models with Optimal Planning Proficiency.
CoRR, 2023

Grounding Classical Task Planners via Vision-Language Models.
CoRR, 2023

Task and Motion Planning with Large Language Models for Object Rearrangement.
IROS, 2023

Symbolic State Space Optimization for Long Horizon Mobile Manipulation Planning.
IROS, 2023

SLAP: Spatial-Language Attention Policies.
Proceedings of the Conference on Robot Learning, 2023

2022
Learning to Ground Objects for Robot Task and Motion Planning.
IEEE Robotics Autom. Lett., 2022

GLAD: Grounded Layered Autonomous Driving for Complex Service Tasks.
CoRR, 2022

Robot Task Planning and Situation Handling in Open Worlds.
CoRR, 2022

Visually Grounded Task and Motion Planning for Mobile Manipulation.
Proceedings of the 2022 International Conference on Robotics and Automation, 2022

2021
Learning to Guide Human Attention on Mobile Telepresence Robots with 360 degree Vision.
CoRR, 2021

Planning Multimodal Exploratory Actions for Online Robot Attribute Learning.
Proceedings of the Robotics: Science and Systems XVII, Virtual Event, July 12-16, 2021., 2021

Learning to Guide Human Attention on Mobile Telepresence Robots with 360° Vision.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

2020
Task-Motion Planning for Safe and Efficient Urban Driving.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020


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