Jiannan Chen

Beijing University of Posts and Telecommunications

Papers

Total Citations

H-Index

About

Jiannan Chen is a robotics researcher whose work focuses on enhancing human-robot collaboration through advanced perception and navigation systems. His primary research areas include pedestrian detection, dynamic path planning, and the application of 2D LiDAR technology for service robots. Chen’s most cited paper, "Pedestrian Detection and Tracking Based on 2D Lidar" (2019, 19 citations), proposes a novel algorithm that enables robots to detect and track pedestrians in real time using 2D LiDAR data. This work is crucial for allowing service robots to adapt their movements based on human behavior, improving safety and efficiency in shared environments. By addressing the challenge of dynamic path planning, Chen’s contributions help robots better understand and respond to pedestrian motion states, fostering more intuitive collaboration. His research has implications for autonomous systems in public spaces, such as hospitals, airports, and retail settings, where seamless human-robot interaction is essential. Chen’s work stands out for its practical approach to integrating LiDAR-based perception into real-world robotic applications, laying groundwork for safer and more responsive autonomous systems.