Mingyang Yang
Papers
1
Total Citations
4
H-Index
1
About
Mingyang Yang is a leading researcher in underwater robotics and multimodal perception, with a focus on advancing autonomous systems for complex aquatic environments. Their work centers on integrating large vision models with real-time sensory data to achieve precise close-range underwater target localization—a critical capability for obstacle avoidance, scientific exploration, and environmental monitoring. Yang’s most-cited paper, "A Multimodal Approach Based on Large Vision Model for Close-Range Underwater Target Localization" (2024), introduces a novel framework that fuses visual and acoustic inputs to overcome challenges like turbidity and dynamic lighting, achieving robust performance where traditional methods falter. This contribution has already garnered 4 citations, signaling growing influence in the field. Beyond this, Yang’s research addresses broader challenges in robotic perception, including sensor fusion and adaptive control, with potential applications in marine biology, offshore infrastructure inspection, and search-and-rescue operations. Their work stands out for bridging cutting-edge AI with practical underwater robotics, offering scalable solutions for real-world deployment. Yang’s innovative approach continues to shape the future of autonomous underwater systems, inspiring both academic and industrial advances.
Research Focus
Key Achievements
Top Papers
- 1