Shaobao Li
Papers
2
Total Citations
78
H-Index
2
About
Shaobao Li is a leading researcher in intelligent robotics and autonomous systems, with a primary focus on underwater perception and multi-robot coordination. His most impactful contribution is the development of YOLOv5s-CA, a modified deep learning network that integrates coordinate attention mechanisms for enhanced underwater target detection. This work, published in 2023 and already garnering 76 citations, addresses critical challenges in marine surveillance, aquaculture, and rescue operations by improving detection accuracy in complex, low-visibility underwater environments with limited training data. Li also advances the field of multi-robot systems through his work on finite-time formation control of nonholonomic mobile robots, where he proposed a path-guided control scheme using an extended state observer to compensate for unmeasured velocities and disturbances. This research has direct applications in coordinated autonomous navigation and formation flying. By bridging computer vision and control theory, Li's work enables more reliable and autonomous robotic operations in challenging real-world settings, making him a notable figure in the development of intelligent, perception-driven robotic systems for marine and terrestrial applications.
Research Focus
Key Achievements
Top Papers
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- 2