Xin Weng

Shanghai University of Engineering Science

Papers

Total Citations

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About

Xin Weng is a researcher specializing in autonomous systems and robotic path planning, with a focus on developing advanced optimization algorithms for dynamic environments. Their major contributions lie in enhancing meta-heuristic algorithms for real-time motion planning, particularly through the integration of artificial potential fields with multi-objective optimization techniques. Weng's most-cited work, "Dynamic path planning for mobile robots based on artificial potential field enhanced improved multiobjective snake optimization (APF-IMOSO)" (2024), has garnered 27 citations, demonstrating its impact on improving navigation efficiency in complex settings. This study introduces a novel hybrid approach that combines the snake optimizer with potential field methods to address local minima and path smoothness issues. Additionally, their recent work, "MESO: a multi-strategy enhanced snake optimizer applied to autonomous vehicle motion planning" (2025), extends these principles to autonomous driving, showcasing Weng's commitment to bridging theoretical optimization with practical vehicular applications. Through these contributions, Weng has advanced the state of the art in autonomous navigation, offering scalable solutions for both mobile robots and self-driving vehicles.