Yunzhe Shang
Papers
1
Total Citations
3
H-Index
1
About
Yunzhe Shang is a researcher focused on autonomous navigation and path planning for unmanned ground vehicles (UGVs), particularly in challenging unstructured environments. His most cited work introduces an improved A-star algorithm that enhances UGV mobility by establishing a kinematic model and optimizing longitudinal motion control. This contribution addresses critical limitations in traditional path planning methods, enabling safer and more efficient navigation in complex, non-uniform terrains. With his 2024 paper already garnering early citations, Shang’s work is gaining traction among robotics and autonomous systems researchers. By integrating practical kinematic constraints into algorithmic design, he bridges the gap between theoretical path planning and real-world deployment—a key step toward robust field robotics. His research holds promise for applications in agriculture, disaster response, and off-road autonomous transport. As the demand for intelligent ground vehicles grows, Shang’s innovations in adaptive, environment-aware navigation position him as an emerging contributor to the next generation of autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1