Guangmei Wu

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About

Guangmei Wu is a researcher specializing in intelligent automation systems and robotic parking technologies, with a focus on optimizing efficiency in compact urban environments. Her most-cited work, "Considering the influence of queue length on performance improvement for a new compact robotic automated parking system" (2019), has garnered 18 citations, establishing her as a contributor to the field of automated parking infrastructure. In this study, Wu systematically analyzes how queue length dynamics impact system throughput and operational performance, proposing novel design improvements that reduce wait times and enhance space utilization in high-density parking facilities. Her research bridges industrial engineering and robotics, offering practical solutions for smart city development. Wu’s contributions are particularly notable for addressing real-world constraints in automated system design, such as spatial limitations and traffic flow management. By integrating queueing theory with robotic system optimization, she provides a framework that can be applied to broader logistics and warehousing automation. Her work is frequently referenced by engineers and urban planners seeking to implement efficient, space-saving automated parking systems, underscoring her impact on both academic research and practical infrastructure innovation.