Ya Xie

Papers

Total Citations

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About

Ya Xie is a leading researcher in mobile robotics, with a primary focus on path planning and optimization using evolutionary algorithms. Her most impactful work addresses a critical challenge in autonomous navigation: improving the speed and reliability of pathfinding in static environments. In her highly cited 2020 paper (53 citations), Xie introduced an improved genetic algorithm that overcomes the slow convergence and local optimum pitfalls of traditional methods, enabling mobile robots to compute shorter, more efficient paths. This contribution has been foundational for researchers seeking robust, real-time navigation solutions. Xie also authored a comprehensive review (2020, 6 citations) that systematically surveys the state of genetic algorithm applications in mobile robot path planning, serving as a key reference for newcomers and experts alike. Her work bridges theoretical algorithm design with practical robotic deployment, demonstrating how adaptive search techniques can enhance autonomous systems. With a growing citation footprint, Ya Xie continues to shape the field of intelligent robotics, offering both novel methodologies and critical syntheses of existing knowledge.