Jiyuan Shi

University Town of Shenzhen, Tsinghua University

Papers

Total Citations

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About

Jiyuan Shi is an emerging robotics researcher whose work sits at the intersection of motion control, reinforcement learning, and legged locomotion. Their research addresses some of the most technically demanding challenges in robot locomotion, from the precise balance control of bipedal systems to the robust navigation of quadrupedal robots across unpredictable terrains. In their 2022 study on bipedal balance, Shi tackled the formidable problem of one-foot standing — a task complicated by a reduced support polygon and the kinematic coupling between the center of mass and a swinging limb — proposing an innovative Three-Particle Model Predictive Control framework that has since earned 9 citations. Building on this foundation, their 2024 work on quadrupedal locomotion introduced a risk-averse reinforcement learning approach, integrating privileged distillation and scene modeling to enhance robustness across challenging real-world terrains, accumulating 7 citations in a short time. Collectively, Shi's contributions reflect a sophisticated command of both classical control theory and modern machine learning paradigms. For students and researchers in humanoid robotics, autonomous systems, or robot learning, Jiyuan Shi's growing body of work represents an important and timely voice in advancing reliable, adaptive legged locomotion.