Chao‐Bo Yan

Xi'an Jiaotong University

Papers

2

Total Citations

13

H-Index

2

About

Chao-Bo Yan is a researcher whose work bridges the critical domains of 3D perception and autonomous mobile robotics. His primary research areas include 3D point cloud registration, path planning, and autonomous navigation. Yan’s most significant contribution is the development of **3DMNDT**, a novel 3D multi-view registration method based on the Normal Distributions Transform. This work directly addresses a fundamental limitation of traditional NDT—its susceptibility to accumulated error when applied to multi-view registration—by introducing a robust framework that improves accuracy for complex 3D scenes. With 11 citations, this paper has already established a notable impact in the field of computer vision and robotics. In parallel, Yan has advanced autonomous navigation for factory environments by proposing an efficient method for extracting the shortest Dubins path specifically optimized for short-distance maneuvers. This work is critical for the real-time operation of Autonomous Mobile Robots (AMRs), offering a direct and computationally efficient solution to a classic path-planning problem. Through these contributions, Yan is shaping the future of how robots perceive their environment and navigate it efficiently.

Research Focus

Key Achievements

2
H-Index
2
Papers
13
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
3DMNDT: 3D Multi-View Registration Method Based on the Normal Distributions Transform
11 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: Xi'an Jiaotong University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago