Papers
3
Total Citations
10
H-Index
2
About
Yufeng Gu’s research career is defined by a deep commitment to advancing robotic perception and manipulation, spanning from foundational dynamics to cutting-edge virtual reality applications. His work primarily focuses on three interconnected areas: mobile robot locomotion, outdoor scene understanding using LiDAR, and robotic grasping within the metaverse. Gu’s early contribution, “Dynamic Modeling for Obstacle Negotiation of Wheel-Legged Robot and Analysis on Its Influential Factors” (2010, 6 citations), established a rigorous framework for analyzing how wheel-legged robots traverse complex terrains, a critical step for autonomous navigation. He later advanced autonomous vehicle perception with “Outdoor Scene Understanding Based on Multi-Scale PBA Image Features and Point Cloud Features” (2019, 3 citations), where he introduced the novel Panoramic Bearing Angle (PBA) image model to enhance LiDAR-based point cloud classification, enabling more robust environmental interpretation. Most recently, Gu has pushed the boundaries of human-robot interaction with “LWD-IUM: A Lightweight Detector for Advancing Robotic Grasp in VR-Based Industrial and Underwater Metaverse” (2025, 1 citation), a pioneering work that develops a compact detector for precise robotic manipulation in virtual reality environments. This latest achievement highlights his ability to bridge physical robotics with immersive digital worlds, positioning him as a forward-thinking researcher whose work continues to shape the future of intelligent, autonomous systems.
Research Focus
Key Achievements
Top Papers
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