Ruixue Li

Hosei University, China University of Mining and Technology

Papers

Total Citations

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About

Ruixue Li is a leading researcher in intelligent warehousing systems and autonomous navigation for industrial environments. Her work centers on optimizing automated material handling and advancing robotic perception in challenging settings like underground coal mines. Li’s most influential contribution is her development of travel time models for the rack-moving mobile robot (RMMR) system, a novel parts-to-picker automated warehousing solution. This foundational 2019 paper, with 25 citations, provides critical analytical models for system design and throughput estimation, enabling more efficient warehouse operations. She has also made significant strides in autonomous navigation, authoring a highly cited 2022 study on an improved LeGO-LOAM algorithm for underground coal mine map construction. This work, garnering 22 citations, directly supports China’s national strategy for intelligent mining by enhancing the environmental perception and real-time positioning capabilities of robots and unmanned vehicles in GPS-denied, hazardous environments. Li’s research bridges the gap between theoretical optimization and practical deployment, with her contributions to both warehouse logistics and mining automation demonstrating a clear impact on the future of industrial robotics.