Guanyu Ding
Papers
3
Total Citations
37
H-Index
3
About
Guanyu Ding is a robotics researcher specializing in autonomous navigation, perception, and intelligent manipulation for industrial and service robots. His work centers on developing practical, lightweight solutions for real-world robotic systems, particularly in logistics and public health. Ding’s most cited paper introduces SORLA, a real-time localization strategy for LiDAR-guided autonomous robots using artificial landmarks, which compensates for odometry drift during high-speed or sharp-turning maneuvers—a critical advancement for agile warehouse robots. He also proposed a systematic pallet identification and picking approach (PILA) that combines deep learning with vehicle alignment algorithms, enabling forklift robots to autonomously detect and engage pallets with high precision. In response to the COVID-19 pandemic, Ding designed a UVC surface disinfection robot featuring coverage path planning optimized for low-computational edge devices, addressing urgent needs for automated sanitation in cold-chain and hospital environments. With over 37 citations across his key publications, Ding’s contributions demonstrate a strong commitment to bridging theoretical robotics with deployable, cost-effective automation solutions. His work is particularly notable for its emphasis on real-time performance and practical applicability, making him a rising voice in the field of intelligent robotic systems.
Research Focus
Key Achievements
Top Papers
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