Lie Guo

Papers

Total Citations

H-Index

About

Lie Guo’s research lies at the intersection of intelligent vehicle systems, computer vision, and autonomous navigation, with a particular focus on pedestrian safety and mobile robot path planning. In his influential 2010 study on pedestrian detection and tracking with monocular vision—cited 8 times—Guo addressed a critical challenge in advanced driver-assistance systems: not merely detecting pedestrians but predicting their trajectories through dynamic tracking to enable collision avoidance. This work has implications for surveillance, robotics, and autonomous driving. More recently, Guo has advanced mobile robot navigation with a 2022 paper on an A* algorithm enhanced with an adaptive search strategy. By tackling the traditional A* algorithm’s limitations—specifically its inefficient node expansion and unnecessary path bends—Guo’s approach improves path smoothness and computational efficiency, offering practical benefits for real-world autonomous navigation. Though his citation counts are modest, Guo’s contributions are foundational, bridging theoretical algorithm design with applied safety and mobility solutions. His work continues to inform researchers developing more responsive, intelligent vehicles and robots.