Jialuo Yang

Zhengzhou University of Light Industry

Papers

1

Total Citations

27

H-Index

1

About

Jialuo Yang is a robotics researcher whose work focuses on the intersection of autonomous navigation and intelligent firefighting systems. Their most-cited paper, "An Indoor Autonomous Inspection and Firefighting Robot Based on SLAM and Flame Image Recognition" (2023, 27 citations), addresses a critical challenge in modern safety technology: enabling robots to operate effectively in complex, hazardous indoor environments. Yang’s key contribution lies in integrating Simultaneous Localization and Mapping (SLAM) with flame image recognition, allowing a robot to autonomously navigate through smoke-filled, high-temperature spaces with multiple turns and obstacles while accurately detecting and responding to fires. This work bridges the gap between theoretical robotics and practical emergency response, offering a scalable solution for reducing human risk during indoor fire accidents. By tackling the dual problems of environmental mapping and real-time fire identification, Yang has laid groundwork for next-generation autonomous safety robots. Their research is particularly valuable for students and engineers interested in applying SLAM, computer vision, and sensor fusion to life-saving technologies, demonstrating how robotics can directly impact public safety and disaster management.

Research Focus

Key Achievements

1
H-Index
1
Papers
27
Total Citations
27
Avg Citations/Paper
🏆 Most Cited Paper
An Indoor Autonomous Inspection and Firefighting Robot Based on SLAM and Flame Image Recognition
27 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: Zhengzhou University of Light Industry

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago