Xu Sheng
Papers
1
Total Citations
10
H-Index
1
About
Xu Sheng is a prominent researcher in mobile robotics, with a primary focus on autonomous navigation and path planning. His work addresses critical challenges in real-world robotic movement, particularly the local minimum problem in potential field methods and odometer drift in wall-following algorithms. His most cited paper, "Path planning of a mobile robot using an improved mixed-method of potential field and wall following" (2023, 10 citations), introduces a novel hybrid approach that combines the strengths of both techniques to enhance path efficiency and robustness in dynamic environments. This contribution has been recognized for its practical applicability, offering a more reliable solution for mobile robots operating in cluttered or uncertain spaces. Xu Sheng’s research bridges the gap between theoretical algorithms and real-world implementation, making significant strides in improving autonomous navigation systems. His work continues to influence the development of safer and more efficient robotic path planning, with growing impact in the field of intelligent robotics and automation.
Research Focus
Key Achievements
Top Papers
- 1