Zhenao Yu

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About

Zhenao Yu is a researcher focused on intelligent optimization algorithms for autonomous mobile robot navigation. His work primarily addresses the computationally challenging, NP-hard problem of path planning, with a particular emphasis on multi-objective scenarios that balance competing factors like path length, safety, and energy efficiency. Yu’s major contributions lie in enhancing classic evolutionary algorithms to solve these complex problems more effectively. His most cited work, “Solving the multi-objective path planning problem for mobile robot using an improved NSGA-II algorithm” (2024, 64 citations), demonstrates a significant impact by refining a well-known genetic algorithm for real-world robotic applications. Additionally, his earlier paper on an improved artificial bee colony algorithm for multi-objective path planning (2022, 15 citations) further establishes his expertise in adapting nature-inspired metaheuristics for autonomous navigation. Through these contributions, Yu has advanced the practical deployment of intelligent optimization in robotics, offering more robust and efficient solutions for mobile robot autonomy.