Xiaokang Dai
Papers
1
Total Citations
1
H-Index
1
About
Xiaokang Dai is a pioneering researcher at the intersection of robotics, energy systems, and artificial intelligence, with a primary focus on enhancing the performance and efficiency of legged robots. His most notable contribution lies in the development of an AI-enabled bumpless transfer control strategy for legged robots equipped with hybrid energy storage systems (HESS). This work addresses a critical challenge in robotics: the torque instability that occurs when switching between driving and regenerative braking modes. By leveraging artificial intelligence to smooth these transitions, Dai’s approach significantly improves motion stability and energy efficiency, directly impacting the viability of advanced legged robots for real-world applications. His 2024 paper on this topic has already garnered attention, accumulating citations that underscore its relevance in the rapidly evolving field of robotic locomotion. Dai’s research bridges control theory, energy management, and machine learning, offering a practical solution to a longstanding engineering problem. His work is particularly influential for students and researchers exploring the integration of AI with power systems in robotics, marking him as a rising contributor to sustainable and high-performance robotic design.
Research Focus
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Top Papers
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