Yongji Guan
Papers
2
Total Citations
17
H-Index
2
About
Yongji Guan is a rising researcher in robotics and control systems, with a focus on distributed optimization and neural dynamics for multi-robot coordination. His work centers on developing robust, real-time control frameworks that integrate both kinematics and dynamics, enabling complex multi-robot systems to operate efficiently under time-varying constraints. Guan’s most cited paper, “Distributed Optimal Control of Multiple Serial Robot Systems With Kinematics and Dynamics Based on Discrete Neural Dynamics” (2024, 11 citations), introduces a novel discrete neural dynamics approach for controlling multiple serial robot systems, addressing the limitations of purely kinematic methods in industrial applications. His follow-up work, “Robust Neural Dynamics for Distributed Time-Varying Optimization With Application to Multi-Robot Systems” (2024, 6 citations), advances the field by tackling time-varying optimization problems with dynamic constraints, a critical step toward practical deployment in uncertain environments. Though early in his career, Guan’s contributions are already shaping the next generation of distributed robotic control, offering scalable and robust solutions that bridge theoretical optimization with real-world multi-agent systems. His research holds particular promise for manufacturing, autonomous fleets, and cooperative manipulation tasks.
Research Focus
Key Achievements
Top Papers
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