About

Zherong Pan is a robotics and computational researcher whose work spans robot motion planning, deformable object simulation, and multi-agent navigation. His research bridges the gap between physical modeling and algorithmic efficiency, developing methods that make complex robotic tasks computationally tractable in real-world settings. Pan's most recognized contribution is his pioneering work on robot motion planning for liquid pouring (2016, 34 citations), which introduced optimization-based trajectory planning guided by physical fluid simulation — a notably challenging problem due to the highly deformable nature of liquids. He has also made significant strides in accelerating deformable object simulation using CNN-based dimensionality reduction (2020, 31 citations), enabling real-time performance for thin-shell materials. His research on manipulating multiple objects (2022, 28 citations) addresses critical challenges in warehouse automation and service robotics. Beyond single-robot systems, Pan has advanced multi-robot coordination through decentralized graph neural network-based navigation (2021, 16 citations) and robust trajectory optimization via ADMM frameworks (2022, 15 citations). His broader portfolio encompasses contact-implicit trajectory optimization, planar linkage design, and multi-objective robot co-design, reflecting a researcher consistently pushing the boundaries of intelligent, physically-aware robotic systems.

Research Focus

Key Achievements

8
H-Index
18
Papers
189
Total Citations
11
Avg Citations/Paper
🏆 Most Cited Paper
Robot Motion Planning for Pouring Liquids
34 citations · 2016
📈 Most Prolific Year: 2022 (5 Papers)
🤝 Key Collaborators: 28
🏛 Institutions: University of North Carolina at Chapel Hill, University of Illinois Urbana-Champaign, KLA (United States), Tencent (China), Bellevue Hospital Center

Top Papers

  1. 1
  2. 2
  3. 3
  4. 4
  5. 5
  6. 6
  7. 7
  8. 8
  9. 9
  10. 10

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago