Leilei Meng
Papers
6
Total Citations
122
H-Index
6
About
Leilei Meng is a leading researcher in mobile robot navigation, whose work has fundamentally advanced the field of autonomous path planning. His primary research focuses on developing intelligent optimization algorithms to solve the computationally complex (NP-hard) path planning problem, ensuring robots can navigate safely and efficiently. Meng’s major contributions center on enhancing classic evolutionary algorithms, particularly the artificial bee colony (ABC) algorithm, for multi-objective scenarios. He has pioneered novel hybrid approaches, such as the HABC-GA, which integrates a genetic augmented exploration mechanism to guarantee safe and smooth trajectories, and the GAO-RRT*, a variant of the rapidly-exploring random tree star (RRT*) algorithm that achieves both low path cost and fast convergence. His work has garnered significant attention, with his most cited paper, "Solving the multi-objective path planning problem for mobile robot using an improved NSGA-II algorithm," accumulating 64 citations. Meng has also addressed critical real-world applications, including post-disaster rescue operations, where he modeled the path planning problem as a variant of the traveling salesman problem (TSP) with limited survival time. Through a series of impactful publications from 2022 to 2025, Leilei Meng continues to shape the future of intelligent, autonomous navigation.
Research Focus
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Top Papers
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