Yinghao Li
Papers
2
Total Citations
67
H-Index
2
About
Yinghao Li is a researcher whose work bridges swarm intelligence and autonomous underwater vehicle (AUV) design, with a focus on multi-objective optimization. His key research areas include swarm robotics, particle swarm optimization (PSO), and shape optimization for marine vehicles. Li’s major contribution lies in developing an improved grouping strategy for swarm robots searching for multiple targets in unknown environments, as detailed in his most-cited paper (2017, 44 citations). This work enhances collaborative efficiency by integrating constriction factors into PSO, enabling robots to dynamically form groups after stochastic movement iterations. Additionally, Li has tackled optimal shape design for AUVs using multi-objective PSO (2019, 23 citations), balancing hydrodynamic performance and structural constraints. His research demonstrates practical impact by addressing real-world challenges in autonomous exploration and underwater vehicle efficiency. With a citation count exceeding 67 across his top papers, Li’s work is recognized for advancing swarm coordination algorithms and their application to robotics and marine engineering. His achievements highlight a commitment to solving complex, multi-objective problems in dynamic environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2