Mingqing Liu

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About

Mingqing Liu is a robotics and localization researcher whose work addresses critical challenges in multi-robot cooperative localization (MRCL) and indoor positioning systems. His primary research areas span collaborative robotics, sensor fusion, and precision localization technologies for both outdoor and indoor environments. Liu's most significant contribution is the development of a laser rangefinder-based baseline measurement system for outdoor MRCL, which overcomes the limitations of low-accuracy GPS by equipping unmanned ground vehicles (UGVs) with shared cameras and laser rangefinders. His trilateral localization algorithm, combining least-squares matrix and gradient descent methods, has been cited 4 times since 2024. In his 2025 work on resonant beam phase-based passive localization (RBPPL), Liu addresses the growing demand for high-accuracy indoor positioning in Internet of Everything (IoE) and metaverse applications, optimizing a system for autonomous robots and virtual reality. His 2023 paper on cloud computing-enabled MRCL further demonstrates his commitment to practical deployment in shipping, production, and logistics. With a total of 7 citations across his most-cited works, Liu's research represents a systematic approach to bridging the gap between theoretical localization algorithms and real-world multi-robot systems operating under GPS-denied or GPS-degraded conditions.