Zhe Chen

陈喆 • Postdoctoral Scientist, Amazon Robotics. Previously Monash University.

cz.jpeg

Amazon Robotics

North Reading, MA

I am a Postdoctoral Scientist at Amazon Robotics working on efficient motion planning and coordination of mobile robots in warehouse environments. My research focuses on Multi-Agent Path Finding (MAPF), Heuristic Search, and Planning algorithms that enable large teams of robots to coordinate seamlessly.

I received my PhD in Computer Science from Monash University in 2024, advised by Prof Daniel Harabor and Prof Peter Stuckey.

Research Interests

  • Multi-Agent Path Finding: Developing scalable algorithms for coordinating large teams of robots
  • Heuristic Search: Creating efficient search algorithms for path planning problems
  • Planning and Scheduling: Designing algorithms that handle dynamic environments and uncertainties
  • Traffic Flow Optimization: Optimizing robot movement in dense environments
  • Real-time Planning: Developing algorithms that can adapt to changing conditions

My research has practical applications in warehouse robotics, autonomous vehicle coordination, and any scenario requiring efficient coordination of multiple autonomous agents. I am passionate about bridging the gap between theoretical advances and real-world deployment.

I actively contribute to the research community through organizing workshops (AAAI Workshop on Multi-Agent Path Finding), competitions (Grid-Based Path Planning Competition, League of Robot Runners), and serving on program committees for top-tier venues including AAAI, ICAPS, and SoCS.

System Demonstrations

My research translates into practical systems and tools. Here are demonstrations of some key projects:

League of Robot Runners Competition
A competitive platform for multi-agent path finding algorithms with real-time constraints and dynamic environments.
Tracking Progress in Multi-Agent Path Finding
Visualization system showing real-time progress tracking and performance metrics for MAPF algorithms.
Flatland Challenge: Rail Planning System
Our winning solution for the 2020 Flatland Challenge, demonstrating scalable train coordination in complex rail networks.

News

Feb 01, 2025 Two Papers Accepted at AAAI 2025
Jan 21, 2025 Started my new position as Postdoctoral Scientist at Amazon Robotics! 🤖
Jan 15, 2025 Organizing the AAAI-25 Workshop on Multi-Agent Path Finding (MAPF)! Join us for the latest advances in MAPF research. Workshop website
Jun 18, 2024 🎓 Successfully defended my PhD thesis! Grateful to my advisors Daniel Harabor and Peter Stuckey, and excited for the next chapter at Amazon Robotics.
Jun 01, 2024 🏆 Our League of Robot Runners competition received the ICAPS 2024 Best System Demonstration Award Honorable Mention!
Feb 07, 2023 Organizing the AAAI-23 Workshop on Multi-Agent Path Finding (MAPF)! Bringing together researchers to advance the field of multi-agent coordination.

Selected publications

  1. The League of Robot Runners Competition: Goals, Designs, and Implementation
    Shao-Hung Chan, Zhe Chen, Teng Guo, and 6 more authors
    In ICAPS 2024 System’s Demonstration track, 2024
  2. Traffic Flow Optimisation for Lifelong Multi-Agent Path Finding
    Zhe Chen, Daniel Harabor, Jiaoyang Li, and 1 more author
    In Thirty-Eighth AAAI Conference on Artificial Intelligence, AAAI 2024, Thirty-Sixth Conference on Innovative Applications of Artificial Intelligence, IAAI 2024, Fourteenth Symposium on Educational Advances in Artificial Intelligence, EAAI 2014, February 20-27, 2024, Vancouver, Canada, 2024
  3. Planning and Execution in Multi-Agent Path Finding: Models and Algorithms
    Yue Zhang, Zhe Chen, Daniel Harabor, and 2 more authors
    In Proceedings of the Thirty-Fourth International Conference on Automated Planning and Scheduling, ICAPS 2024, Banff, Alberta, Canada, June 1-6, 2024, 2024
  4. Beyond Pairwise Reasoning in Multi-Agent Path Finding
    Bojie Shen, Zhe Chen, Jiaoyang Li, and 3 more authors
    In Proceedings of the Thirty-Third International Conference on Automated Planning and Scheduling, Prague, Czech Republic, July 8-13, 2023, 2023
  5. Tracking Progress in Multi-Agent Path Finding
    Bojie Shen, Zhe Chen, Muhammad Aamir Cheema, and 2 more authors
    CoRR, 2023
  6. Integrated Task Assignment and Path Planning for Capacitated Multi-Agent Pickup and Delivery
    Zhe Chen, Javier Alonso-Mora, Xiaoshan Bai, and 2 more authors
    IEEE Robotics Autom. Lett., 2021
  7. Scalable Rail Planning and Replanning: Winning the 2020 Flatland Challenge
    Jiaoyang Li, Zhe Chen, Yi Zheng, and 5 more authors
    In Proceedings of the Thirty-First International Conference on Automated Planning and Scheduling, ICAPS 2021, Guangzhou, China (virtual), August 2-13, 2021, 2021
  8. Anytime Multi-Agent Path Finding via Large Neighborhood Search
    Jiaoyang Li, Zhe Chen, Daniel Harabor, and 2 more authors
    In Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI 2021, Virtual Event / Montreal, Canada, 19-27 August 2021, 2021