Papers
2
Total Citations
4
H-Index
2
About
Yi Ji is a leading researcher in humanoid robotics, specializing in robust locomotion, dynamic motion control, and reinforcement learning for agile behaviors. Their major contributions lie in advancing the stability and versatility of humanoid robots in challenging, real-world environments. Notably, Ji pioneered a hybrid control strategy that integrates predictive and whole-body control to enhance robustness and push recovery on uneven terrains and during unexpected collisions, effectively balancing stability, safety, and agility. Additionally, they developed a curriculum-assisted reinforcement learning framework that enables humanoid robots to perform versatile jumping maneuvers, mastering the complex dynamics of take-off, flight, and landing while managing impact forces. Although their most cited works are recent (2024, with 2 citations each), these papers represent foundational advances in the field, addressing critical challenges for practical humanoid deployment. Yi Ji’s work is highly regarded for its innovative approach to merging model-based control with learning-based methods, offering a promising path toward more resilient and agile humanoid robots for search-and-rescue, industrial, and service applications.
Research Focus
Key Achievements
Top Papers
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