Fujun Pei
Papers
4
Total Citations
34
H-Index
3
About
Fujun Pei is a robotics and autonomous systems researcher whose work centers on simultaneous localization and mapping (SLAM) — a fundamental challenge in enabling mobile robots to navigate unknown environments independently. His research has made meaningful contributions to the development of distributed SLAM architectures, addressing critical computational bottlenecks that limit real-world deployment of autonomous navigation systems. Pei's most influential work focuses on reformulating classical SLAM algorithms — including FastSLAM and Extended Kalman Filter-based SLAM — within distributed frameworks that dramatically reduce computational overhead while preserving estimation accuracy. His 2014 paper on an improved FastSLAM system tackled the long-standing problem of exponential computation growth as feature points change, earning 12 citations, while his companion study on distributed particle filter SLAM demonstrated that comparable localization performance could be achieved in just one-fifth of the processing time of centralized approaches. He has further refined these methods by incorporating advanced optimization techniques such as particle swarm optimization and decorrelated EKF structures to combat particle impoverishment and improve robustness. Collectively accumulating over 34 citations, Pei's body of work offers practical, computationally efficient solutions that bring autonomous robot navigation closer to reliable real-world application.
Research Focus
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Top Papers
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