Xuefeng Dai
Papers
20
Total Citations
165
H-Index
7
About
Xuefeng Dai is a leading researcher in multi-robot systems and autonomous mobile robotics, with a career spanning foundational surveys to cutting-edge optimization algorithms. His work centers on three critical challenges: cooperative exploration, path planning, and task allocation. Dai’s most influential paper, “Cooperative exploration based on supervisory control of multi-robot systems” (43 citations), established a framework for coordinated robot teams. He advanced practical applications with “Application of Improved Moth-Flame Optimization Algorithm for Robot Path Planning” (27 citations), introducing a novel metaheuristic that significantly improves global path optimization for mobile robots—a cornerstone for real-world deployment. His contributions also include automatic recharging strategies for cleaning robots and hybrid AI approaches, such as BP neural networks optimized by genetic algorithms for multi-robot task allocation. Dai has further enriched the field with key surveys on autonomous navigation and SLAM, integrating soft computing techniques to overcome traditional filter limitations. With over 135 total citations across his top works, Dai’s research bridges theoretical innovation and industrial application, making him a pivotal figure in advancing intelligent, autonomous robot systems.
Research Focus
Key Achievements
Top Papers
- 1Cooperative exploration based on supervisory control of multi-robot systems43 citations · 2016
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- 3Automatic Recharging Path Planning for Cleaning Robots12 citations · 2021
- 4Autonomous Navigation for Wheeled Mobile Robots-A Survey12 citations · 2007
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