Papers
2
Total Citations
38
H-Index
2
About
Yongming Wu is an emerging researcher in artificial intelligence, with a primary focus on intelligent robotics, numerical optimization, and autonomous path planning for unmanned aerial vehicles (UAVs) and ground robots. His work addresses the limitations of traditional methods in solving complex nonlinear problems, a critical challenge in modern AI. Wu’s most cited paper, a 2018 review on the key technologies, application fields, and development trends of intelligent robots, has garnered 35 citations, establishing a foundational overview for researchers entering this domain. More recently, he introduced the Graduate Student Evolutionary Algorithm, a novel metaheuristic published in 2025, specifically designed for 3D UAV and robot path planning. Though still early in its citation life, this work represents a significant contribution to optimization-based AI, offering a fresh approach to autonomous navigation. Wu’s research is particularly valuable for students and researchers seeking efficient, nature-inspired algorithms to tackle real-world robotic challenges, bridging the gap between theoretical optimization and practical deployment.
Research Focus
Key Achievements
Top Papers
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