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About

Songyi Zhang is a leading researcher in mobile robotics, specializing in path planning and autonomous navigation for wheeled robots in complex environments. Their most significant contribution is the "Global-Local Coupling Two-Stage Path Planning" (CTSP) method, which addresses the nonlinear optimization challenge of robot path planning by combining global optimal solutions with local adjustments—a work that has garnered 78 citations and become a foundational reference in the field. Zhang further advanced kinodynamic local planning with the "Long-Term Dynamic Window Approach," enabling differential wheeled robots to navigate safely through both static and crowded dynamic environments, earning 18 citations for its practical impact. Additional notable work includes the automatic generation of hierarchical topological maps using straight skeletons for indoor navigation, and parametric path optimization techniques that enhance collision risk reduction and smoothness. By tackling real-world constraints like computational efficiency and kinodynamic feasibility, Zhang’s research bridges theoretical optimization with deployable robotic systems, making their work essential for students and engineers developing next-generation autonomous mobile robots.