Papers
1
Total Citations
68
H-Index
1
About
Qingli Yan is a leading researcher in autonomous maritime robotics, specializing in multi-robot systems, coverage path planning, and search and rescue (SAR) operations. Their most cited work, "A Multi-Robot Coverage Path Planning Method for Maritime Search and Rescue Using Multiple AUVs" (2022, 68 citations), addresses the critical challenge of efficiently coordinating multiple Autonomous Underwater Vehicles (AUVs) to scan vast ocean areas for missing targets. By developing novel algorithms that optimize sonar image acquisition and robot trajectories, Yan’s research significantly improves the speed and accuracy of underwater SAR missions—a vital contribution to disaster response and marine safety. This work has been widely recognized for its practical impact, bridging theoretical path planning with real-world deployment constraints. Yan’s achievements underscore a deep commitment to advancing autonomous systems for humanitarian and environmental applications, making their research essential reading for engineers and scientists working on multi-agent coordination, marine robotics, and intelligent search strategies.
Research Focus
Key Achievements
Top Papers
- 1