Fangkai Cai

Chengdu Technological University

Papers

1

Total Citations

6

H-Index

1

About

Fangkai Cai is a robotics researcher whose work focuses on advancing autonomous navigation and perception for industrial inspection applications. Their primary research areas include simultaneous localization and mapping (SLAM), multi-sensor fusion, and mobile robotics for hazardous environments. Cai’s most notable contribution is the development of an improved SLAM algorithm that integrates inertial measurement unit (IMU) data with visual information, specifically designed for substation inspection robots. This work addresses critical limitations of manual inspection—such as high labor intensity, low efficiency, and safety risks—by enabling robots to reliably navigate complex indoor environments like substation rooms and chemical plants. The algorithm enhances localization accuracy and robustness in visually degraded settings, a key challenge for real-world deployment. With 6 citations to date, this 2024 paper has already attracted attention from researchers working on industrial automation and field robotics. Cai’s work represents a meaningful step toward safer, more efficient autonomous inspection systems, with potential applications extending to other confined or hazardous industrial spaces where human entry is risky.

Research Focus

Key Achievements

1
H-Index
1
Papers
6
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
An improved SLAM algorithm for substation inspection robot based on the fusion of IMU and visual information
6 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: Chengdu Technological University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago