Yique Deng

Sun Yat-sen University

Papers

1

Total Citations

30

H-Index

1

About

Yique Deng is a robotics researcher whose work centers on autonomous navigation, sensor fusion, and simultaneous localization and mapping (SLAM) for mobile robots. Their most notable contribution is the development of a large-scale navigation method that fuses RTK-GPS with LiDAR SLAM, enabling robots to maintain high localization accuracy across both indoor and outdoor environments—a critical challenge for real-world autonomous systems. This work, published in 2018 and garnering 30 citations, addresses the robustness limitations of single-sensor perception by integrating global positioning with local mapping, allowing seamless transitions between disparate settings. Deng’s research has practical implications for logistics, field robotics, and autonomous vehicles, where reliable navigation in mixed environments is essential. By tackling the fusion of heterogeneous sensors, they have advanced the field’s understanding of how to achieve consistent, centimeter-level localization under varying conditions. Their contributions continue to influence the design of perception systems for next-generation autonomous mobile robots, bridging the gap between controlled indoor settings and unstructured outdoor terrains.

Research Focus

Key Achievements

1
H-Index
1
Papers
30
Total Citations
30
Avg Citations/Paper
🏆 Most Cited Paper
Large-Scale Navigation Method for Autonomous Mobile Robot Based on Fusion of GPS and Lidar SLAM
30 citations · 2018
📈 Most Prolific Year: 2018 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: Sun Yat-sen University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago