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About

Xuefei Liu is a pioneering roboticist whose work bridges the gap between legged locomotion and adaptive control, with a focus on wheel-legged bipedal systems and rescue robotics. Her research centers on developing intelligent, stable, and versatile robots capable of navigating complex environments—from disaster zones to vertical surfaces. Liu’s major contributions include a comprehensive review of wheel-legged biped robots (2024, 50 citations), which has become a foundational resource in the field, and a novel adaptive dynamic optimal balance control method (2024, 16 citations) that enhances stability in real-time. She also advanced SLAM technology with a lightweight loop closure detection algorithm (2021, 8 citations) that uses deep learning for efficient feature matching. Her work on a parallel mobile rescue robot, employing a PSO-CPG algorithm for invariably horizontal control (2023, 3 citations), demonstrates her commitment to practical, life-saving applications. Most recently, Liu designed a dual-body negative pressure ground-wall transition robot (2025, 2 citations), expanding climbing robots’ capabilities for high-altitude operations. Her interdisciplinary approach—combining control theory, bio-inspired design, and deep learning—positions her as a rising leader in mobile robotics, with her research directly impacting autonomous navigation, disaster response, and industrial inspection.