Yanqi Wu

Southeast University, Eindhoven University of Technology

Papers

Total Citations

H-Index

About

Yanqi Wu is a robotics and automation researcher whose work bridges intelligent systems, computer vision, and practical engineering applications. Their key research areas include unmanned aerial systems (UAS), deep learning for agricultural robotics, and automated laboratory instrumentation. Wu’s most impactful contribution is a two-stage automatic method for bridge coating inspection using a collision-tolerant UAS, published in 2022 with 38 citations—demonstrating significant influence in infrastructure maintenance and field robotics. This work addresses critical safety and efficiency challenges in structural health monitoring. Wu also developed a premium tea-picking robot that integrates deep learning and computer vision for precise leaf detection, a 2024 publication with 11 citations that tackles labor shortages in China’s culturally and economically vital tea industry. Earlier, Wu contributed to robotic sample preparation based on magnetic separation (2016, 4 citations), showcasing versatility across domains. These achievements highlight Wu’s commitment to advancing automation in both industrial and agricultural contexts, with a clear trajectory toward high-impact, real-world solutions. Their work is particularly relevant for researchers interested in field robotics, vision-guided manipulation, and the intersection of traditional industries with modern AI.