Papers
1
Total Citations
33
H-Index
1
About
Yu Ling is a leading researcher in autonomous underwater robotics, with a primary focus on simultaneous localization and mapping (SLAM) in challenging subsea environments. Their most influential work, "Active Bathymetric SLAM for autonomous underwater exploration" (2022), has garnered 33 citations and introduced a novel framework that integrates real-time bathymetric data with active path planning. This contribution enables autonomous underwater vehicles (AUVs) to intelligently navigate and map unknown terrains, significantly improving efficiency and accuracy in deep-sea surveys. Ling’s approach addresses critical limitations in traditional SLAM by leveraging sonar-derived depth measurements to reduce drift and enhance loop closure detection, a breakthrough with direct applications in oceanography, offshore infrastructure inspection, and environmental monitoring. Their research bridges the gap between theoretical robotics and practical marine exploration, offering scalable solutions for long-duration missions. By demonstrating how active perception can optimize both mapping fidelity and energy consumption, Ling has set a new standard for intelligent AUV autonomy. This work is widely cited by peers developing next-generation underwater systems, cementing Ling’s reputation as a key innovator in field robotics and autonomous exploration.
Research Focus
Key Achievements
Top Papers
- 1Active Bathymetric SLAM for autonomous underwater exploration33 citations · 2022