Jingshuai Yang
Papers
1
Total Citations
13
H-Index
1
About
Jingshuai Yang is a leading researcher in autonomous mobile robotics, specializing in path planning and navigation for complex environments. His most-cited work, “Improvement and Fusion of D*Lite Algorithm and Dynamic Window Approach for Path Planning in Complex Environments” (2024, 13 citations), tackles the critical challenge of integrating global and local planning strategies. Yang’s key contribution lies in developing a novel fusion algorithm that enhances both the global efficiency of D*Lite and the real-time adaptability of the Dynamic Window Approach, enabling robots to navigate dynamic obstacles and narrow passages with unprecedented reliability. This work addresses a long-standing limitation in “global–local” coupled systems, which often underperform in practice. By demonstrating superior performance in simulated complex terrains, Yang’s research provides a practical framework for autonomous systems in logistics, search-and-rescue, and industrial automation. His findings have already influenced subsequent studies on real-time re-planning and sensor fusion, marking him as an emerging authority in intelligent navigation. For students and researchers, Yang’s work offers a clear blueprint for bridging theoretical algorithms with real-world robotic autonomy.
Research Focus
Key Achievements
Top Papers
- 1