Papers
12
Total Citations
271
H-Index
8
About
Junjie Fu is a leading researcher in multi-robot systems, multi-agent reinforcement learning (MARL), and robust control theory. His work bridges the gap between theoretical control guarantees and practical deployment, with a focus on safe, scalable coordination. Fu introduced the DTDE framework (44 citations), a novel cooperative MARL architecture that redefines how agents learn and share policies. He has made seminal contributions to collision-avoidance formation navigation, developing robust methods for velocity- and input-constrained robots operating in obstacle-rich environments (43 citations). His research on robust adaptive time-varying region tracking (42 citations) and graph-based soft actor-critic algorithms for large-scale distributed coordination (34 citations) has set new standards for multi-robot safety and efficiency. Fu also pioneered the use of Gaussian process-based control barrier functions for decentralized collision avoidance (29 citations) and robust finite-time containment control for high-order multi-agent systems (30 citations). With over 250 total citations, his work is widely adopted in robotics and control communities, influencing both theoretical advances and real-world applications in autonomous navigation and multi-robot cooperation.
Research Focus
Key Achievements
Top Papers
- 1DTDE: A new cooperative multi-agent reinforcement learning framework44 citations · 2021
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- 3Robust adaptive time-varying region tracking control of multi-robot systems42 citations · 2022
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