Nan Guo

Henan University of Science and Technology

Papers

Total Citations

H-Index

About

Nan Guo is a robotics researcher whose work focuses on advancing autonomous navigation and environmental perception for mobile robots, particularly in dynamic and hazardous settings. His key contributions span path planning, obstacle detection, and specialized robot design. Guo’s most cited paper, "PRM-D* Method for Mobile Robot Path Planning" (2023, 33 citations), introduces a hybrid algorithm that combines probabilistic roadmap methods with D* lite to achieve high planning success rates, fast computation, and dynamic obstacle avoidance—critical for real-world navigation tasks. He also developed "A Hierarchical Clustering Obstacle Detection Method Applied to RGB-D Cameras" (2023, 2 citations), addressing limitations in deep learning-based vision systems by using traditional clustering for robust, real-time obstacle detection in complex environments. Earlier, Guo contributed to "Design and Research of Small Crawler Fire Fighting Robot" (2018, 16 citations), where he employed virtual prototyping to create a robot tailored for firefighting scenarios, enhancing firefighter safety. Through these works, Guo demonstrates a commitment to practical, efficient solutions for mobile robotics, with his path planning method already gaining traction among researchers tackling dynamic navigation challenges.