Papers
1
Total Citations
3
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1
About
Yifan Lu is an emerging researcher specializing in robotic perception, multimodal sensor fusion, and semantic mapping, with a particular focus on applying advanced computer vision and autonomous systems technologies to complex real-world environments such as construction sites. His most notable work, "Real-time Multimodal Fusion and Semantic Mapping for Robotic Tower Crane Perception" (2026), addresses a critical gap in the field of construction robotics — the inadequacy of conventional Simultaneous Localization and Mapping (SLAM) methods when deployed on dynamic, crane-mounted platforms where sensor motion is abrupt and environmental semantics are essential for safe operation. By developing a system capable of real-time perception in rapidly changing construction environments, Lu bridges the worlds of robotics, civil engineering automation, and artificial intelligence in a meaningful and practical way. Though early in his career, his work has already garnered recognition within the research community, accumulating citations that signal growing interest in crane automation and intelligent construction systems. Lu's contributions position him as a promising voice in the push toward safer, smarter, and more autonomous infrastructure development workflows.
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Top Papers
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