Zhaoxiang Li

Papers

Total Citations

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About

Zhaoxiang Li is a robotics researcher whose work centers on adaptive control, optimal regulation, and the dynamic modeling of legged and wheeled robotic systems. His most cited paper, "Adaptive optimal output regulation for wheel-legged robot Ollie: A data-driven approach" (2023, 26 citations), addresses a critical challenge in real-world robotics: maintaining control performance when a robot’s dynamics shift due to factors like non-ideal motor characteristics or unmodeled loads. By developing an adaptive optimal output regulation (AOOR) framework, Li introduced a data-driven method that enables robots to autonomously adjust their control strategies without requiring precise prior models. This contribution is significant for enhancing the robustness and autonomy of wheel-legged robots operating in unpredictable environments. Li’s work bridges theoretical control theory with practical robotic applications, offering solutions that improve stability and performance under varying conditions. His research has implications for field robotics, where adaptability is essential. As a rising scholar, Li’s focus on data-driven, adaptive approaches positions him at the forefront of next-generation robotic control systems.