Sanqing Qu

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About

Sanqing Qu is a robotics researcher focused on intelligent autonomous systems for urban mobility, particularly in parking automation and robot navigation. Their key research areas include self-localization, mechanical design, and sensor integration for autonomous parking robots. Qu's major contribution is the development of low-cost, high-accuracy positioning frameworks for parking robots, as demonstrated in their most-cited work, "Self-Localization of Parking Robots Using Square-Like Landmarks" (2018, 6 citations). This paper innovatively leverages common parking lot structures—such as pillars and corners—as landmarks, offering a practical solution to reduce reliance on expensive sensors. Additionally, Qu led the design of the "ITDP-Robot" (2019, 2 citations), an intelligent transport dispatch parking robot prototype that addresses urban parking shortages through a novel mechanical structure adaptable to various vehicle sizes. This work showcases Qu's ability to bridge theoretical localization methods with real-world hardware implementation. While citation counts are modest, Qu's research is notable for its applied focus on solving tangible urban challenges, contributing to the growing field of autonomous valet systems and smart city infrastructure.