Da Ke

Wuhan University of Technology, Wuhan University of Science and Technology

Papers

Total Citations

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About

Da Ke is a researcher whose work bridges intelligent control systems and mobile robotics, with a focus on enhancing precision and efficiency in autonomous navigation and actuation. His key research areas include iterative learning control, fuzzy logic systems, and path planning algorithms. Ke’s major contributions are demonstrated in his work on a fuzzy PD-type iterative learning controller for pneumatic muscle actuators, which improved trajectory tracking in soft robotic systems—a critical advancement for compliant and safe human-robot interaction. He also developed a variable-step-length A* algorithm for mobile robot path planning, which overcomes the limitations of traditional A* by producing shorter, more efficient paths with fewer steps, directly addressing real-world navigation challenges. With over 14 citations across his most-cited papers, Ke’s research has influenced both theoretical developments and practical applications in robotics. His notable work on the variable-step-length A* algorithm stands out for its innovative approach to optimizing path smoothness and computational efficiency, making it a valuable reference for researchers in autonomous systems.