Ruofan Lv
Papers
2
Total Citations
62
H-Index
2
About
Ruofan Lv’s research centers on multi-robot systems, with a particular focus on autonomous underwater vehicles (AUVs) operating in complex, unknown environments. His major contributions lie in developing bio-inspired coordination algorithms for multi-AUV hunting—a critical challenge in marine robotics and defense. Lv’s most influential work, a 2015 paper with 56 citations, introduces a novel hunting algorithm based on a bio-inspired neural network that enables multiple AUVs to efficiently track and capture targets without prior environmental knowledge. This approach elegantly mimics biological neural dynamics to solve real-time path planning and coordination. Building on this, Lv further advanced the field by incorporating ocean current effects into multi-AUV hunting strategies, addressing a practical yet often overlooked environmental factor that significantly impacts underwater vehicle performance. His work bridges theoretical neural network models with tangible robotic applications, offering scalable solutions for autonomous underwater surveillance, search-and-rescue, and environmental monitoring. Through these contributions, Lv has established himself as a key figure in bio-inspired multi-robot coordination, demonstrating how nature-inspired algorithms can overcome the challenges of dynamic, uncertain underwater environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2A multi-AUV hunting algorithm with ocean current effect6 citations · 2015