Yilin Mo

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About

Yilin Mo is a researcher whose work centers on robotics, motion planning, and autonomous systems, with a particular focus on dynamic environment interaction. Their most notable contribution lies in the development of algorithms for moving target interception, a critical challenge in fields ranging from autonomous navigation to defense. In their 2022 paper, "Moving Target Interception Considering Dynamic Environment," Mo proposed a novel approach that uses polynomial fitting to predict a target's future trajectory, enabling a wheeled mobile robot to successfully intercept it in real-time. This work, which has garnered 13 citations, demonstrates a practical application of predictive modeling to enhance robotic responsiveness in unpredictable settings. Mo's research bridges theoretical control systems and real-world implementation, offering valuable insights for students and engineers working on autonomous vehicles, surveillance, or robotic assistance. By addressing the complexities of dynamic obstacles and target motion, Mo contributes to making autonomous systems more adaptive and reliable, with potential impacts on logistics, search-and-rescue, and intelligent transportation.