Papers
1
Total Citations
34
H-Index
1
About
Dr. Xing Lan has made significant contributions to the field of intelligent robotics, with a primary focus on autonomous navigation and path planning. Their most impactful work addresses a critical bottleneck in mobile robotics: the slow convergence and inefficiency of traditional ant colony algorithms for global path planning. In their highly cited 2021 paper, Dr. Lan proposed a groundbreaking hybrid algorithm that fuses the A-star heuristic with ant colony optimization. This innovation dramatically accelerates search speeds and reduces iteration counts, enabling robots to find optimal routes in complex environments far more efficiently. With 34 citations, this work has become a key reference for researchers tackling real-time navigation challenges. Dr. Lan’s research bridges the gap between theoretical optimization and practical robotic applications, offering a robust solution for autonomous systems in logistics, exploration, and industrial automation. Their work stands as a testament to the power of algorithmic synergy, providing a faster, more reliable foundation for the next generation of intelligent mobile robots.
Research Focus
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