Junliang Li

Shandong University of Science and Technology

Papers

Total Citations

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About

Junliang Li is a leading researcher in mobile robotics and indoor positioning systems, with a focus on cost-effective, infrastructure-light solutions. His major contributions center on developing robust, Wi-Fi-based indoor positioning systems that eliminate the need for expensive sensors like infrared or cameras, making autonomous navigation more accessible for industrial and home automation. Li’s most-cited work, "A robust mobile robot indoor positioning system based on Wi-Fi" (2020, 34 citations), demonstrates a practical, high-accuracy approach that reduces hardware complexity. His earlier paper, "Mobile Robot Indoor Positioning System Based on K-ELM" (2019, 20 citations), further advances the field by addressing poor accuracy and system instability through a kernel extreme learning machine framework. Together, these works have garnered over 50 citations, reflecting their influence in robotics and sensor fusion. Li’s research is notable for bridging the gap between theoretical positioning algorithms and real-world deployment, offering scalable solutions that lower barriers to entry for robotics applications. His achievements highlight a commitment to democratizing mobile robot technology through innovative, low-cost positioning methods.