Yuxuan Shen

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About

Yuxuan Shen is a researcher whose work lies at the intersection of robotics, control theory, and energy-efficient sensing. His primary research areas include mobile robot localization, recursive filtering, and sensor management under energy constraints. Shen’s major contribution is the development of a recursive filtering framework for mobile robot localization using energy harvesting sensors—a novel approach that allows robots to operate sustainably by absorbing ambient energy. This work, published in 2021 and cited 13 times, addresses the critical challenge of maintaining accurate localization when sensor energy is intermittent or limited. In 2023, Shen advanced this line of inquiry with a study on measurement outlier-resistant mobile robot localization, earning 6 citations for its practical robustness. His research is particularly notable for bridging theoretical filtering techniques with real-world robotic applications, offering solutions that enhance autonomy in energy-constrained environments. Shen’s achievements are significant for students and researchers interested in resilient, low-power robotic systems, as his work provides a foundation for future developments in sustainable robotics and sensor-driven navigation.