Shaojie Wang

Xiamen University

Papers

1

Total Citations

16

H-Index

1

About

Dr. Shaojie Wang is a robotics researcher whose work centers on autonomous navigation and perception in challenging environments. His primary contributions lie in developing novel sensing and detection methods for robots operating on unstructured terrain, a critical area for field robotics. His most cited work, "Novel Laser-Based Obstacle Detection for Autonomous Robots on Unstructured Terrain" (2020), introduces an innovative approach that applies the Sobel operator—a classic image-processing edge-detection technique—directly to 3D laser point clouds. This method significantly enhances the ability of autonomous robots to identify obstacles in irregular, off-road settings where traditional detection often fails. With 16 citations, this paper has established a foundation for subsequent research in rugged-terrain navigation. Dr. Wang’s work bridges the gap between computer vision algorithms and LiDAR-based perception, offering practical solutions for real-world robotic autonomy. His research is particularly relevant for applications in search-and-rescue, planetary exploration, and agricultural robotics, where reliable obstacle detection is paramount.

Research Focus

Key Achievements

1
H-Index
1
Papers
16
Total Citations
16
Avg Citations/Paper
🏆 Most Cited Paper
Novel Laser-Based Obstacle Detection for Autonomous Robots on Unstructured Terrain
16 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: Xiamen University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago