Jielong Guo

Quanzhou Normal University, Tan Kah Kee Innovation Laboratory

Papers

Total Citations

H-Index

About

Jielong Guo is a researcher advancing the frontiers of intelligent robotics and human-robot interaction (HRI). His work centers on developing more intuitive and autonomous robotic systems, with key contributions in motion planning and non-verbal communication. Guo’s most cited paper, “Dynamic path planning fusion algorithm with improved A* algorithm and dynamic window approach” (2024), has garnered 22 citations by addressing a critical challenge: enabling robots to navigate dynamic environments efficiently. By fusing global path planning with real-time obstacle avoidance, this work enhances robotic autonomy in complex settings. In his earlier review, “Hand and Arm Gesture-based Human-Robot Interaction: A Review” (2022, 10 citations), Guo provided a comprehensive analysis of non-verbal HRI, emphasizing the importance of natural, intuitive communication—a cornerstone for collaborative robotics. This review has become a valuable resource for researchers seeking to bridge the gap between human intent and robotic action. Through these contributions, Guo is shaping a future where robots are not only smarter navigators but also more responsive partners, laying groundwork for safer, more seamless human-robot collaboration in industrial and service applications.