Papers
2
Total Citations
18
H-Index
2
About
Fu Zhen is a leading researcher in whole-body loco-manipulation and humanoid robot stabilization, with a focus on enabling dynamic, coordinated control for complex robotic systems. Their major contributions include pioneering reinforcement learning (RL) frameworks for wheeled-quadrupedal manipulators, achieving omni-directional task-space pose tracking that seamlessly coordinates floating base and robotic arm movements—a critical step toward real-world deployment in unstructured environments. Additionally, Zhen developed a force-feedback-based whole-body stabilizer for position-controlled humanoid robots, addressing the fundamental challenge of maintaining balance and trajectory tracking under external disturbances. This work, with 9 citations each, has provided foundational tools for robust humanoid locomotion. Zhen’s research bridges the gap between simulation and reality, offering scalable solutions for robots that must manipulate objects while navigating complex terrains. Their achievements are particularly notable for advancing the practical viability of wheeled-quadrupedal platforms, which combine mobility and manipulation in a single system. For students and researchers, Zhen’s work exemplifies how RL and control theory can be fused to solve real-world robotics challenges, making them a key figure in the next generation of autonomous, physically capable machines.
Research Focus
Key Achievements
Top Papers
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