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About

Xiaotong Shen is a robotics researcher specializing in autonomous navigation, sensor integration, and cooperative localization for mobile systems operating in complex, cluttered environments. Her work addresses critical challenges in enabling robots to perceive, plan, and move safely alongside dynamic obstacles, including walking humans and other moving agents. A key contribution is her development of scalable cooperative localization methods that function with minimal sensor configurations, reducing hardware complexity while maintaining robust positioning accuracy. She has also advanced state estimation techniques for moving objects from a moving robotic base, a fundamental capability for indoor mobile manipulation. Her research on obstacle-guided informed planning improves path efficiency in cluttered spaces by focusing sampling on regions that promise better solutions, building upon algorithms like Informed RRT* and BIT*. Additionally, Shen has led system integration efforts for omnidirectional robotic platforms, combining fast EtherCAT-based control with sophisticated software architectures to achieve real-time navigation performance. With her most cited works accumulating over 20 citations, Shen’s contributions are shaping practical, real-world deployment of autonomous robots in human-centric environments.