Ray Zirui Xu

I'm a Ph.D. candidate in Aerospace Engineering at University of Michigan, advised by Vasileios Tzoumas. My research interests lie in the intersection of optimization, control, and robotics, and my goal is to enable large-scale distributed collaborative autonomy in complex tasks, for vehicles, drones, and mobile sensors. In particular, my work investigates:

• Theories: Provably near-optimal tools for combinatorial optimization and online combinatorial learning;
• Algorithms: Learning and coordination algorithms for effective and efficient online decision-making in dynamic and adversarial environments;
• Applications: Real-world implementation of coordination algorithms onboard resource-constrained agents for communication- and computation-demanding tasks.

Previously, I received an M.S. in Electrical & Computer Engineering from Georgia Tech in 2020 and a B.Eng. in Automation from Northeastern University (China) in 2018. I was also a Research Intern at Honda Research Institute in San Jose, CA for summer 2024.

email  /  google scholar  /  linkedin

• 07/24/2024: Paper on self-configurable multi-agent networks with simultaneous action and neighbor selection accepted to CDC 2024.
• 05/20/2024: I start my first day in San Jose, CA this summer as a Research Intern at HRI. Feel free to drop by and hang out with me if you're around - I'd love to catch up and share what I've been working on!
• 01/22/2024: Paper on intelligently leveraging untrustworthy external commands for multi-robot coordination in unstructured environments accepted to ACC 2024.
• 08/31/2023: Paper Resource-Aware Simulator for Decentralized Active Perception with Multiple Robots accepted to IROS 2023 Workshop on Advances in Multi-Agent Learning - Coordination, Perception, and Control.
• 07/28/2023: Paper Online and Robust Intermittent Motion Planning in Dynamic and Changing Environments accepted to IEEE Transactions on Neural Networks and Learning Systems (TNNLS).

Journal Papers

1. Communication- and Computation-Efficient Distributed Decision-Making in Multi-Robot Networks
   Zirui Xu*, Sandilya Sai Garimella*, Vasileios Tzoumas
   under review, 2024.
   arxiv


2. Online and Robust Intermittent Motion Planning in Dynamic and Changing Environments
   Zirui Xu, George P. Kontoudis, Kyriakos G. Vamvoudakis
   IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023.
   paper / simulation video


3. Online Submodular Coordination with Bounded Tracking Regret: Theory, Algorithm, and Applications to Multi-Robot Coordination
   Zirui Xu, Hongyu Zhou, Vasileios Tzoumas
   IEEE Robotics and Automation Letters (RA-L), 2023.
   arxiv / code

Conference Papers

1. Performance-Aware Self-Configurable Multi-Agent Networks: A Distributed Submodular Approach for Simultaneous Coordination and Network Design
   Zirui Xu, Vasileios Tzoumas
   IEEE Conference on Decision and Control (CDC), 2024. Invited Paper.
   arxiv


2. Leveraging Untrustworthy Commands for Multi-Robot Coordination in Unpredictable Environments: A Bandit Submodular Maximization Approach
   Zirui Xu*, Xiaofeng Lin*, Vasileios Tzoumas
   American Control Conference (ACC), 2024.
   arxiv


3. Resource-Aware Simulator for Decentralized Active Perception with Multiple Robots
   Sandilya Sai Garimella, Zirui Xu, Vasileios Tzoumas
   Workshop on Advances in Multi-Agent Learning - Coordination, Perception, and Control
   IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2023.


4. Efficient Online Learning with Memory via Frank-Wolfe Optimization: Algorithms with Bounded Dynamic Regret and Applications to Control
   Hongyu Zhou, Zirui Xu, Vasileios Tzoumas
   IEEE Conference on Decision and Control (CDC), 2023.
   arxiv


5. Bandit Submodular Maximization for Multi-Robot Coordination in Unpredictable and Partially Observable Environments
   Zirui Xu, Xiaofeng Lin, Vasileios Tzoumas
   Robotics: Science and Systems (RSS), 2023.
   arxiv / code / simulation videos / presentation


6. Resource-Aware Distributed Submodular Maximization: A Paradigm for Multi-Robot Decision-Making
   Zirui Xu, Vasileios Tzoumas
   IEEE Conference on Decision and Control (CDC), 2022. Invited Paper.
   arxiv / code / presentation


7. Online, Model-Free Motion Planning in Dynamic Environments: An Intermittent, Finite Horizon Approach with Continuous-Time Q-Learning
   George P. Kontoudis, Zirui Xu, Kyriakos G. Vamvoudakis
   American Control Conference (ACC), 2020.
   pdf / simulation video / presentation

Book Chapters

1. RRT-QX: Real-Time Kinodynamic Motion Planning in Dynamic Environments with Continuous-Time Reinforcement Learning
   George P. Kontoudis, Kyriakos G. Vamvoudakis, Zirui Xu
   Brain and Cognitive Intelligence-Control in Robotics, ed. B. Wei, Chapter 1, CRC Press, 2022.
   book chapter / pdf / video

• Graduate Student Instructor: AEROSP 341 - Aircraft Dynamics, Winter 2024.
• Graduate Student Instructor: AEROSP 584 - Navigation and Guidance: From Perception to Control, Fall 2022.

• President of Graduate Student Advisory Committee (GSAC), Department of Aerospace Engineering, University of Michigan, 2023-24.
• Member of DEI Committee, Department of Aerospace Engineering, University of Michigan, 2022-23.

last updated: Sep 2024 | template from here