Xiaobin Xu

Hohai University

Papers

15

Total Citations

217

H-Index

7

About

Xiaobin Xu is a leading researcher in mobile robotics, specializing in sensor fusion, simultaneous localization and mapping (SLAM), and intelligent control systems. Their work addresses critical challenges in autonomous navigation, particularly for indoor service robots and rehabilitation devices. Xu’s most impactful contribution is an adaptive federated Kalman filter algorithm that solves the problem of inaccurate single-sensor positioning, achieving 50 citations. They have also pioneered a novel calibration method for robot kinematic parameters using an improved manta ray foraging optimization algorithm, which significantly reduces absolute positioning errors in manipulators. In environmental perception, Xu developed a fusion algorithm combining sparse point cloud data with image information for robust object detection in complex scenarios. Their research extends to human-machine interaction, including a hand exoskeleton design for stroke rehabilitation, and path tracking control using model predictive control with adaptive neural-fuzzy inference systems. With over 200 total citations across ten publications, Xu’s comprehensive review of 2D LiDAR SLAM and their work on obstacle modeling for rescue robots demonstrate a sustained commitment to advancing autonomous systems.

Research Focus

Key Achievements

7
H-Index
15
Papers
217
Total Citations
14
Avg Citations/Paper
🏆 Most Cited Paper
An Indoor Mobile Robot Positioning Algorithm Based on Adaptive Federated Kalman Filter
50 citations · 2021
📈 Most Prolific Year: 2021 (5 Papers)
🤝 Key Collaborators: 46
🏛 Institutions: Hohai University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago