Quanbo Yuan

North China Institute of Aerospace Engineering

Papers

Total Citations

258

H-Index

About

Quanbo Yuan is a researcher whose work bridges foundational robotics algorithms with cutting-edge intelligent systems. His most influential contribution, the 2011 paper "Application of Dijkstra algorithm in robot path-planning," has garnered 244 citations and remains a cornerstone reference for efficient path selection in maze-like environments, demonstrating the enduring value of classic algorithmic solutions in robotics. More recently, Yuan has expanded into autonomous driving and human-computer interaction. His 2024 review of 3D object detection for autonomous driving synthesizes critical advances in this rapidly evolving field, while his work on a deep-learning-assisted piezoresistive intelligent glove represents a notable achievement in tactile sensing. This glove, capable of pressure monitoring and object identification through deep learning, showcases Yuan's ability to integrate hardware innovation with artificial intelligence, advancing the humanoid capabilities of modern intelligent devices. From foundational path-planning algorithms to state-of-the-art sensory systems, Yuan's research trajectory reflects a commitment to solving real-world robotic challenges, with his early work continuing to influence new generations of autonomous systems researchers.