Xiaoyan Wen

Beijing University of Civil Engineering and Architecture

Papers

Total Citations

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About

Xiaoyan Wen is a robotics researcher whose work centers on advancing the locomotion capabilities of humanoid robots, with a particular focus on achieving robust, stable walking in real-world environments. Her most notable contribution is an improved model predictive control (MPC) method based on the Divergent Component of Motion (DCM), a framework that simplifies the complex dynamics of bipedal robots. By reformulating the humanoid robot model, Wen’s approach enhances the robot’s ability to maintain balance and recover from external disturbances—a critical requirement for deploying humanoid robots in tasks that replace human labor. This work, published in 2022 and garnering 10 citations, has been recognized for its practical impact on real-time control systems. Wen’s research bridges theoretical control theory and applied robotics, offering a scalable solution for more resilient humanoid platforms. Her achievements underscore a commitment to making humanoid robots safer and more reliable for dynamic, unstructured settings, positioning her as an emerging voice in the field of legged locomotion and autonomous systems.