Papers
1
Total Citations
6
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1
About
Xujie Qin is a researcher specializing in robotics, localization, and state estimation, with a particular focus on set-membership filtering and its application to autonomous systems operating under uncertainty. Their most-cited work, "Single-Beacon Localization for Mobile Robot: A Set Membership Filtering Approach" (2024, 6 citations), addresses a critical challenge in mobile robotics: achieving reliable localization using only a single range-measuring beacon. Qin’s major contribution lies in developing a filtering framework that does not require accurate statistical noise models—a common and limiting assumption in traditional Kalman or particle filters. By leveraging set-membership theory, their approach guarantees bounded estimation errors even when noise statistics are unknown, making it theoretically sound and practically robust for real-world deployment. This work has been recognized for its potential to simplify and reduce the cost of robot navigation systems, particularly in GPS-denied or infrastructure-limited environments. With a growing citation impact, Qin’s research is paving the way for more resilient and accessible localization solutions in mobile robotics and autonomous systems.
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