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About

Xiaoying Du is a robotics and artificial intelligence researcher whose work centers on autonomous navigation, motion planning, and optimization algorithms for robotic systems. With a focus on solving real-world challenges in mobile robot and manipulator path planning, Du has made meaningful contributions to advancing the efficiency and reliability of robotic movement in complex environments. Du's most influential research addresses critical limitations in classical planning algorithms. Her 2022 work on improving Particle Swarm Optimization (PSO) through integration with differential evolution and corporate governance concepts tackled longstanding issues of premature convergence and low accuracy in mobile robot navigation, earning over 55 combined citations across related publications. Her 2023 study on an enhanced RRT*FN framework for robotic manipulators pushed the boundaries of real-time collision avoidance in multi-scenario environments, accumulating 24 citations within its first year — a strong indicator of immediate community impact. Collectively, Du's research reflects a sophisticated blend of bio-inspired computation and sampling-based planning strategies. Her contributions are particularly valuable for researchers developing autonomous systems requiring robust, adaptive navigation in dynamic and constrained settings, positioning her as an emerging voice in intelligent robotics and computational optimization.