Tong Xu

Tong Xu

PhD student for Robotics

George Mason University

RobotiXX Lab

Hello there!

I am currently a senior PhD student in RobotiXX Lab at George Mason University, advised by Prof. Xuesu Xiao. I received my master’s degree from University of Southern California and bachelor’s degree from Nanjing University of Information Science & Technology.

My primary research interests include motion planning, reinforcement learning, and whole-body loco-manipulation. My current work focuses on kinodynamics adaptation across heterogeneous autonomous robot fleets and humanoid robot learning.

Interests

  • Robotics
  • Motion Planning
  • Reinforcement Learning
  • Foundation Models

Education

  • Ph.D. in Computer Science, 2023

    George Mason University

  • M.S. in Computer Science, 2021

    University of Southern California

  • B.E. in Network Engineering, 2017

    Nanjing University of Information Science & Technology

News

Publications

Journal

Autonomous Ground Navigation in Highly Constrained Spaces: Lessons Learned from The Forth BARN Challenge at ICRA 2025

Autonomous Ground Navigation in Highly Constrained Spaces: Lessons Learned from The Forth BARN Challenge at ICRA 2025

X. Xiao, Z. Xu, S. A. Ghani, A. Datar, D. Song, P. Stone, A. Mazen, K. Yazdipaz, I. Mateyaunga, M. Faied, M. Krishnan, Y. Lu, T. Xu, N. Mohammad, W. Kim, J. Reasoner, and N. Bezzo
IEEE Robotics & Automation Magazine (RAM), 2025
Website Paper Dataset
CARoL: Context-aware Adaptation for Robot Learning

CARoL: Context-aware Adaptation for Robot Learning

Z. Hu, T. Xu, X. Xiao, and X. Wang
IEEE Robotics and Automation Letters (RA-L), 2025
Paper
Pietra: Physics-informed evidential learning for traversing out-of-distribution terrain

Pietra: Physics-informed evidential learning for traversing out-of-distribution terrain

X. Cai, J. Queeney, T. Xu, A. Datar, C. Pan, M. Miller, A. Flather, P. R. Osteen, N. Roy, X. Xiao, and Jonathan P. How
IEEE Robotics and Automation Letters (RA-L), 2024
Paper Video

Conference

VertiAdaptor: Online Kinodynamics Adaptation for Vertically Challenging Terrain

VertiAdaptor: Online Kinodynamics Adaptation for Vertically Challenging Terrain

T. Xu, C. Pan, A. Datar, and X. Xiao
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2026
✨Oral Presentation✨
Paper
Traverse the Non-Traversable: Estimating Traversability for Wheeled Mobility on Vertically Challenging Terrain

Traverse the Non-Traversable: Estimating Traversability for Wheeled Mobility on Vertically Challenging Terrain

C. Pan, C. Pan, A. Pokhrel, M. Choulas, M. Nazeri, T. Xu, and X. Xiao
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2026
Paper Video
Adaptive Dynamics Planning for Robot Navigation

Adaptive Dynamics Planning for Robot Navigation

Y. Lu, M. Mao, T. Xu, L. Wang, X. Lin, and X. Xiao
IEEE International Conference on Robotics and Automation (ICRA), 2026
Paper
Verti-Arena: A Controllable and Standardized Indoor Testbed for Multi-Terrain Off-Road Autonomy

Verti-Arena: A Controllable and Standardized Indoor Testbed for Multi-Terrain Off-Road Autonomy

H. Chen, A. Datar, T. Xu, F. Cancelliere, H. Rangwala, M. B. Rao, D. Song, D. Eichinger, and X. Xiao
IEEE International Symposium on Safety Security Rescue Robotics (SSRR), 2025
✨Best Student Presenter Award✨
Paper Video
Decremental Dynamics Planning for Robot Navigation

Decremental Dynamics Planning for Robot Navigation

Y. Lu, T. Xu, L. Wang, N. Hawes, and X. Xiao
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2025
Paper Code Video
Reward Training Wheels: Adaptive Auxiliary Rewards for Robotics Reinforcement Learning

Reward Training Wheels: Adaptive Auxiliary Rewards for Robotics Reinforcement Learning

L. Wang, T. Xu, Y. Lu, and X. Xiao
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2025
Paper Video
VertiSelector: Automatic Curriculum Learning for Wheeled Mobility on Vertically Challenging Terrain

VertiSelector: Automatic Curriculum Learning for Wheeled Mobility on Vertically Challenging Terrain

T. Xu, C. Pan, and X. Xiao
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2025
✨Oral Presentation✨
Paper Code Video
Verti-Bench: A General and Scalable Off-Road Mobility Benchmark for Vertically Challenging Terrain

Verti-Bench: A General and Scalable Off-Road Mobility Benchmark for Vertically Challenging Terrain

T. Xu, C. Pan, M. B. Rao, A. Datar, A. Pokhrel, Y. Lu, and X. Xiao
Robotics: Science and Systems (RSS), 2025
✨Spotlight✨
Website Paper Code Dataset Video
Reinforcement learning for wheeled mobility on vertically challenging terrain

Reinforcement learning for wheeled mobility on vertically challenging terrain

T. Xu, C. Pan, and X. Xiao
IEEE International Symposium on Safety Security Rescue Robotics (SSRR), 2024
✨Oral Presentation✨
Paper Code

Preprint

CAR: Cross-Vehicle Kinodynamics Adaptation via Mobility Representation

CAR: Cross-Vehicle Kinodynamics Adaptation via Mobility Representation

T. Xu, C. Pan, and X. Xiao
under review
Paper

Experience

 
 
 
 
 
RobotiXX Logo

Graduate Research Assistant

RobotiXX

May 2024 – Present Fairfax
  • Research in off-road navigation, reinforcement learning, and foundation models
  • Leading the Verti-Bench for rapid kinodynamics adaptation cross different types of vehicles in off-road navigation scenario
 
 
 
 
 
George Mason University Logo

Graduate Teaching Assistant

George Mason University

Aug 2023 – May 2025 Fairfax
  • Designed student lab contents involving data structure, led weekly lab recitations and office hours
  • Created grading scripts and managed a team of 8 undergraduate teaching assistants
 
 
 
 
 
H2X Lab Logo

Research Intern

H2X Lab

May 2022 – Aug 2022 Boston
  • DeepVO - Visual Odometry with Deep Learning
  • OpenGuide - A Scalable Human-Like Guidance System for Travelers with Visual Impairment

Projects

*
All Deep Learning Visual Odometry

DeepVO

Reproduced Deep Visual Odometry architecture by integrating a pretrained FlowNetSimple model with LSTM. Achieved 14.8% performance improvement through epoch optimization and 8.4% improvement through hyperparameter tuning in the loss function, evaluated on KITTI and nuScenes datasets using translation and rotation RMSE metrics.
Code Presentation

Cone Detection

Implemented Faster R-CNN for cone detection by integrating Region Proposal Network with Fast R-CNN. Achieved 37.4% higher recall rate compared to YOLOv3 on a cone-annotated dataset, demonstrating superior detection performance.
Code Presentation Report

OpenGuide

A Scalable Human-Like Guidance System for Travelers with Visual Impairment.
Code Website

Contact

  • txu25@gmu.edu
  • 4400 University Dr, Fairfax, VA 22030
  • RobotiXX Lab