Falin Qi

China Academy of Railway Sciences

Papers

3

Total Citations

21

H-Index

2

About

Falin Qi is a robotics researcher whose work focuses on intelligent inspection systems for critical infrastructure, particularly in high-speed rail and construction environments. Qi’s most cited paper (2023, 15 citations) introduces a novel obstacle avoidance system for high-speed railway tunnel lining inspection trains, fusing 3D LiDAR with 2D camera machine vision technology. By integrating ORB-SLAM3 with normal distributions, this work significantly enhances the collision prevention capabilities of robotic arms during high-speed tunnel inspections—a critical safety advancement for modern rail infrastructure. Qi’s earlier research (2016) laid the groundwork for automated construction surface inspection, designing climbing robots capable of crawling on vertical surfaces to perform nondestructive testing of lining defects. A subsequent study applied redundant control theory to dual-pump vacuum adsorption systems, analyzing the safety and reliability of wall-climbing robots for building surface detection. These contributions demonstrate Qi’s sustained focus on robotic mobility, sensing, and safety in challenging environments. With a growing citation record, Falin Qi is establishing a reputation for practical, safety-critical innovations in infrastructure robotics, bridging the gap between advanced perception systems and real-world industrial applications.

Research Focus

Key Achievements

2
H-Index
3
Papers
21
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
Research and Application of the Obstacle Avoidance System for High-Speed Railway Tunnel Lining Inspection Train Based on Integrated 3D LiDAR and 2D Camera Machine Vision Technology
15 citations · 2023
📈 Most Prolific Year: 2016 (2 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: China Academy of Railway Sciences

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago