Papers

2

Total Citations

32

H-Index

2

About

Zihao Wang is a robotics and autonomous systems researcher whose work centers on navigation technologies for unmanned aerial vehicles (UAVs) and heterogeneous robot cooperation, particularly in environments where traditional GPS or GNSS signals are unavailable. His research addresses one of the most pressing challenges in modern robotics: enabling reliable, safe navigation in GPS-denied indoor and complex environments. Wang's most notable contribution is his development of intelligent ground-air cooperative navigation frameworks that leverage visual-aided methods to guide UAVs when satellite signals are inaccessible. Rather than relying solely on computationally expensive onboard hardware — a practical limitation for payload-constrained UAVs — his work innovatively distributes the navigational processing burden between ground and aerial vehicles, demonstrating a smarter, systems-level approach to the problem. His 2021 paper on this cooperative framework has accumulated 25 citations, reflecting growing interest in heterogeneous multi-robot systems, while his earlier 2018 foundational work on ground-aerial vehicle cooperation established the conceptual groundwork for these advancements. Wang's research is particularly relevant to researchers and engineers working on autonomous robotics, drone navigation, and multi-agent systems, offering practical solutions for real-world deployment in warehouses, disaster zones, and other GNSS-restricted environments.

Research Focus

Key Achievements

2
H-Index
2
Papers
32
Total Citations
16
Avg Citations/Paper
🏆 Most Cited Paper
An Intelligent Ground-Air Cooperative Navigation Framework Based on Visual-Aided Method in Indoor Environments
25 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: University of Electronic Science and Technology of China

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago