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About

Chenkun Qi is a robotics researcher whose work spans legged locomotion, mechanism design, and autonomous navigation for multi-legged robotic systems. With expertise encompassing both classical mechanical engineering and modern machine learning approaches, Qi has made substantial contributions to the development of quadruped and hexapod robots capable of operating in challenging real-world environments. Among his most influential contributions is pioneering work on hydraulic quadruped robots, including the "Baby Elephant" platform, where his spring parameter design research (cited over 45 times) helped address the critical trade-off between power efficiency and dynamic performance in hydraulic actuation systems. His extensive work on hexapod robots — covering mechanism design, workspace analysis, and obstacle avoidance — has collectively accumulated over 130 citations, establishing him as a key voice in multi-legged robot autonomy. More recently, Qi co-developed a blind locomotion system integrating Adversarial Motion Priors (AMP) for legged robots, earning 90 citations since 2023 and representing a significant leap toward agile, terrain-adaptive locomotion through reinforcement learning. His research on fault-tolerant gait planning further demonstrates a practical focus on robustness under real-world constraints, making his body of work essential reading for researchers advancing capable, deployable legged robotic systems.