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About

Zhiwei Hao’s research focuses on the intersection of optimal control theory and bipedal robotics, with a particular emphasis on real-time gait generation for walking robots. His most significant contribution is the application of the double generating function method—a novel approach to finite-time linear quadratic optimal control—to enable on-demand, computationally efficient gait synthesis for compass biped robots. This method allows a robot to adjust its step length and walking speed almost instantaneously, reducing on-demand computation time to near zero, which is critical for navigating complex, dynamic environments. Although his citation counts are modest (his top paper has 7 citations), Hao’s work addresses a fundamental challenge in legged locomotion: generating stable, optimal gaits in real time without precomputation. His 2013 paper in *Advanced Robotics* and subsequent studies in 2014 demonstrate how the double generating function method can produce smooth, energy-efficient trajectories for each step, directly supporting real-time control. This work has implications for advancing autonomous bipedal robots in search-and-rescue, service, and rehabilitation applications. Hao’s research is a valuable reference for engineers seeking to bridge optimal control theory with practical, on-the-fly robot motion planning.