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About

Weiguo Wu is a robotics researcher whose work spans mobile robot motion planning, adaptive control, and humanoid locomotion. His most influential contributions focus on the theoretical and practical challenges of wheeled mobile robots (WMRs), particularly addressing time-optimal motion planning under both kinematic and dynamic constraints. Using Newton-Euler dynamic modeling, Wu systematically analyzed the nonholonomic constraints inherent to WMR systems, producing foundational work that has garnered over 25 citations in its primary form. Complementing this, his research on adaptive exponential stabilization introduced continuous time-varying controllers grounded in Lyapunov theory, effectively handling unknown input disturbances in chained-form robot systems — work recognized with 15 citations. Wu has also extended his expertise to humanoid robotics, developing walking pattern generation strategies that leverage zero moment point preview control and waist joint moment compensation to enhance dynamic locomotion performance. His later work on dual-arm mobile robots operating within truss structures reflects a broadening scope toward complex, constrained manipulation environments. Collectively, Wu's research addresses some of the most technically demanding problems in autonomous robot motion, offering rigorous mathematical frameworks that continue to inform both academic study and practical robot system design.