Haozhe ZHANG

Northwestern Polytechnical University

Papers

1

Total Citations

15

H-Index

1

About

Haozhe Zhang is a researcher focused on the critical intersection of autonomous systems and safety, with a primary emphasis on collision avoidance technologies for unmanned aerial vehicles (UAVs). His most cited work, a comprehensive 2023 review of rule-based collision avoidance for autonomous UAVs, has garnered 15 citations, establishing him as a thoughtful synthesizer of foundational methods in this rapidly evolving field. This review systematically categorizes and evaluates rule-based approaches—from geometric and potential field methods to formal logic frameworks—providing a crucial roadmap for researchers and engineers developing safe, reliable drone autonomy. By clarifying the strengths and limitations of deterministic, interpretable strategies against more complex learning-based alternatives, Zhang’s contribution helps guide practical deployment in airspace integration and beyond-visual-line-of-sight operations. His work is particularly valuable for students and practitioners seeking to understand the trade-offs between computational simplicity, verifiability, and robustness in real-world UAV navigation. Through this focused review, Zhang has made a clear, actionable impact on the autonomous systems community, offering a foundational reference that continues to inform both academic research and industrial development in safe drone operations.

Research Focus

Key Achievements

1
H-Index
1
Papers
15
Total Citations
15
Avg Citations/Paper
🏆 Most Cited Paper
A review of rule-based collision avoidance technology for autonomous UAV
15 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: Northwestern Polytechnical University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago