Fu Haolong
Papers
1
Total Citations
5
H-Index
1
About
Fu Haolong is a researcher in autonomous robotics, with a primary focus on unmanned air/ground vehicle (UAV/UGV) cooperative systems. His most cited work, "Vision‐based map building and path planning method in unmanned air/ground vehicle cooperative systems" (2020), addresses critical challenges in multi-robot coordination for search-and-rescue operations. In this study, Haolong proposes mathematical algorithms that enable a UAV to function as a "flying eye," using vision sensors to provide global environmental information to ground vehicles. This integration allows for real-time map building and efficient path planning, significantly enhancing mission effectiveness while reducing human risk. Although his citation count is currently modest at 5, his work represents a foundational step in the development of heterogeneous robot teams for emergency response. Haolong’s research contributes to the broader fields of cooperative robotics, sensor fusion, and autonomous navigation, offering practical solutions for scenarios where rapid, coordinated action is essential. His approach highlights the potential of combining aerial and ground platforms to overcome individual limitations, marking him as an emerging voice in multi-robot systems.
Research Focus
Key Achievements
Top Papers
- 1