Jinsong Li

Technical University of Denmark, University of Science and Technology of China

Papers

Total Citations

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About

Jinsong Li is a robotics researcher whose work spans autonomous navigation, motion planning, and intelligent control systems. His research focuses on advancing the capabilities of mobile robotic platforms, with particular emphasis on making sophisticated navigation technologies accessible and deployable in real-world settings. Li's most cited work, "Simulation Study and PID Tune of Automated Guided Vehicles" (2021, 22 citations), examines the broad applicability of AGV systems across diverse environments — from industrial logistics and manufacturing floors to healthcare facilities and libraries. By investigating PID control tuning through simulation, Li contributed practical insights into how AGVs can be optimized for reliable, autonomous operation across these varied domains. His more recent contribution, "Lightweight Neural Path Planning" (2023, 5 citations), reflects a forward-looking shift in his research agenda. Recognizing that learning-based navigation holds tremendous promise yet faces significant computational barriers, Li explores how neural planning frameworks can be streamlined for deployment on resource-constrained, low-cost robots — a challenge with considerable real-world implications for democratizing autonomous robotics. Together, Li's work bridges classical control theory and modern machine learning, positioning him as a researcher dedicated to making intelligent robotic systems both capable and practically deployable across a wide range of applications.