Yicong Yu

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About

Yicong Yu is a robotics researcher specializing in autonomous navigation and path planning for environmental and public health applications. Their work focuses on developing intelligent algorithms that enable robots to perform critical tasks such as ultraviolet disinfection and surface garbage collection. Yu’s most-cited paper, “UV*: A Boustrophedon Pattern-Based Path Planning and Optimization Strategy for an Ultraviolet Disinfection Robot” (2023, 9 citations), addresses the urgent need for automated disinfection during the COVID-19 pandemic. By introducing a boustrophedon (zigzag) pattern optimized with genetic algorithms, this work improves coverage efficiency and energy use for UV robots, offering a scalable solution for infection control. In another notable contribution, “U*: GA-based path planning algorithm for surface floating garbage cleaning robot” (2023, 3 citations), Yu tackles the global marine debris crisis, designing a genetic algorithm-driven path planner that enhances cleaning robot autonomy. These contributions demonstrate Yu’s commitment to solving pressing real-world problems through robotics, blending algorithmic innovation with practical deployment. Their research is particularly impactful for students and engineers interested in mobile robotics, optimization, and socially beneficial automation.