Axing Xi

Guizhou University

Papers

2

Total Citations

7

H-Index

2

About

Axing Xi is a researcher focused on advancing autonomous multi-robot systems, with a particular emphasis on unmanned air/ground vehicle (UAV/UGV) cooperation. Their work addresses a critical challenge in robotics: enabling heterogeneous platforms to collaborate effectively in complex, real-world environments. Xi’s major contributions lie in developing vision-based mapping and global path planning methods that allow a UAV to act as a “flying eye,” providing aerial situational awareness to guide a ground vehicle. This framework is applied to scenarios like search-and-rescue, where efficiency and reduced human risk are paramount. Their most cited paper (2020, 5 citations) introduces a mathematical approach to cooperative navigation, while a subsequent study (2019, 2 citations) refines target searching and path planning under aerial guidance. Though early in their career, Xi’s work is foundational for integrating perception and control in multi-agent systems, offering practical algorithms for autonomous coordination. This research holds promise for disaster response, surveillance, and logistics, positioning Xi as a rising contributor to the field of cooperative robotics.

Research Focus

Key Achievements

2
H-Index
2
Papers
7
Total Citations
4
Avg Citations/Paper
🏆 Most Cited Paper
Vision‐based map building and path planning method in unmanned air/ground vehicle cooperative systems
5 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: Guizhou University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago