Xueting Li
Papers
2
Total Citations
14
H-Index
2
About
Xueting Li is a researcher specializing in multi-robot systems, with a particular focus on task allocation, path planning, and optimization algorithms. Their work addresses the complex challenge of coordinating multiple robots efficiently within dynamic working environments, a problem of growing importance in industrial automation and autonomous systems. Li's most notable contributions center on developing mathematical models and intelligent algorithms to optimize robot operations. By leveraging classical techniques such as the Floyd algorithm for shortest-path computation and genetic algorithms for solving combinatorial optimization problems, their research establishes robust integer programming frameworks that minimize operational costs while satisfying real-world constraints such as collision avoidance and travel time limitations. These contributions represent meaningful advances in making multi-robot deployments more practical and cost-effective. With a combined citation count of 14 across their leading publications, Li's work has drawn attention from the robotics and operations research communities. Their 2017 paper, the more widely cited of the two, stands out for its dual focus on minimizing fixed and operational robot costs, offering a comprehensive model applicable to real-world logistics and manufacturing scenarios. Li's research provides a valuable foundation for students and engineers seeking to understand intelligent coordination strategies in multi-robot environments.
Research Focus
Key Achievements
Top Papers
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- 2