Jiangfeng Guo
Papers
1
Total Citations
80
H-Index
1
About
Jiangfeng Guo is a leading researcher in robotics and autonomous navigation, with a focus on path planning and motion control. His most-cited work, "Global Dynamic Path Planning Fusion Algorithm Combining Jump-A* Algorithm and Dynamic Window Approach" (2021, 80 citations), introduces a novel fusion algorithm that integrates the Jump-A* method with the Dynamic Window Approach. This innovation addresses critical challenges in robot path planning by achieving both global optimality and path smoothness, optimizing the A* algorithm through jump point search to reduce computational overhead while maintaining real-time adaptability. Guo’s contributions are pivotal for advancing autonomous systems in dynamic environments, offering practical solutions for mobile robots in logistics, exploration, and service applications. His work bridges theoretical optimization with real-world implementation, as evidenced by its citation impact and relevance to ongoing research in intelligent robotics. Beyond this flagship paper, Guo continues to explore efficient navigation strategies, solidifying his reputation as a key contributor to the field of autonomous motion planning.
Research Focus
Key Achievements
Top Papers
- 1