Papers
2
Total Citations
15
H-Index
2
About
Zihui Ren is a researcher specializing in robotics, autonomous navigation, and intelligent optimization algorithms, with a particular focus on applications in hazardous environments such as coal mining. Ren's most notable contribution lies in advancing path planning methodologies for rescue robots, addressing critical challenges in search and rescue operations where human intervention is dangerous or impractical. Ren's signature work centers on the development of a Hybrid Adaptive Artificial Fish Swarm Algorithm (HAAFSA), which tackles well-known limitations of the basic artificial fish swarm algorithm, including imprecise optimal solutions and diminishing convergence efficiency in later computational stages. By designing adaptive enhanced prey behaviors and implementing segmented adaptive strategies for the algorithm's view and step parameters, Ren significantly improved the algorithm's performance and reliability for real-world robot path planning scenarios. This research has garnered citations across the robotics and computational intelligence communities, reflecting its relevance to both theoretical optimization and practical emergency response applications. Ren's work contributes to the broader goal of deploying autonomous robotic systems in life-threatening environments, potentially saving lives in mining disasters. For students interested in swarm intelligence, metaheuristic optimization, or rescue robotics, Ren's research offers a valuable intersection of algorithmic innovation and applied engineering.
Research Focus
Key Achievements
Top Papers
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- 2