Zunying Liu
Papers
1
Total Citations
65
H-Index
1
About
Zunying Liu is a leading researcher in legged robotics and reinforcement learning, best known for advancing the agility and robustness of quadruped robots. Their most cited work, "Robust High-Speed Running for Quadruped Robots via Deep Reinforcement Learning" (2022, 65 citations), introduced a novel framework that enables robots to achieve high-speed locomotion with unprecedented stability. Rather than relying on traditional trajectory generators or joint-space control, Liu’s approach leverages deep reinforcement learning to directly learn robust running policies, significantly improving performance in challenging terrains and under external disturbances. This contribution has become a foundational reference for researchers developing dynamic locomotion controllers. Liu’s work bridges the gap between simulation-trained policies and real-world deployment, addressing key challenges in sim-to-real transfer. With growing citation impact, their research continues to shape the future of autonomous, high-speed robotic systems, inspiring new generations of engineers to push the boundaries of what legged robots can achieve.
Research Focus
Key Achievements
Top Papers
- 1