Xiaofu Zou

Beihang University

Papers

1

Total Citations

2

H-Index

1

About

Xiaofu Zou is a researcher in robotics and intelligent maintenance systems, with a focus on optimizing inspection and resource allocation in complex industrial environments. His work centers on developing path planning methods for multi-robot systems, particularly in the context of aero-engine fleet maintenance. Zou’s major contribution is a novel multi-robot formation reuse strategy that enhances inspection efficiency by allowing robots to be dynamically reassigned across tasks, reducing downtime and resource waste. His most-cited paper, "A path planning method for robot-aided aero-engine fleet inspection considering resource reuse strategy" (2022), introduces a two-level reuse framework that coordinates robot formations to deliver inspection resources effectively. While his citation count is still growing—with 2 citations to date—this work lays foundational groundwork for scalable, cost-effective automation in aerospace maintenance. Zou’s research is notable for its practical application to real-world fleet operations, bridging the gap between theoretical robotics and industrial needs. His contributions are particularly relevant for students and researchers interested in multi-robot coordination, resource optimization, and the future of autonomous inspection systems in high-stakes environments.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
A path planning method for robot-aided aero-engine fleet inspection considering resource reuse strategy
2 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: Beihang University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago