Shukun Wu

Guangxi University of Science and Technology, Shanghai Jiao Tong University

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About

Shukun Wu is a robotics researcher whose work bridges perception, sensing, and autonomous control. His primary research areas include sensor fusion, computer vision, and robotic control systems, with a particular focus on enabling robots to operate reliably in complex, real-world environments. Wu’s most significant contribution is a novel method for detecting glass walls using a combination of LiDAR and ultrasonic sensors—a critical challenge in indoor robotics, since standard LiDAR cannot perceive transparent surfaces. This work, published in 2021, has already garnered 6 citations, highlighting its practical importance for navigation and safety in modern architecture. In a separate highly cited project, Wu developed a tracking and control system for the RoboMaster competition robot, achieving real-time object detection at over 100 frames per second by fusing traditional computer vision with neural network methods. This system, cited 4 times, demonstrates his ability to deliver robust, high-speed solutions for competitive and applied robotics. Wu’s work is notable for its direct impact on real-world robotic perception and autonomous targeting, making him a rising figure in applied robotics and sensor integration.