Papers
3
Total Citations
60
H-Index
2
About
Yongping He is a researcher specializing in mobile robotics, sensor fusion, and intelligent localization systems. His work focuses on cost-effective and robust methods for environment mapping, object identification, and robot positioning—critical enablers for autonomous navigation in industrial and indoor settings. He’s best known for developing a fusion approach combining ultra-wideband (UWB) and short-range 2D LiDAR to achieve cost-effective mobile robot mapping, a contribution that has garnered 42 citations. He also advanced dynamic object identification and localization by integrating laser and RFID sensors, addressing the computational and robustness limitations of vision-based methods. His research on particle filter-based positioning further improved robot accuracy in complex environments. With a citation count exceeding 60 across his most-cited works, He’s work is recognized for balancing affordability with performance, making autonomous systems more accessible. His contributions are particularly valuable for students and engineers seeking practical, sensor-fusion solutions for real-world robotics challenges.
Research Focus
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Top Papers
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