Papers
3
Total Citations
8
H-Index
2
About
Jingdan Li is pioneering the integration of autonomous robotics into the challenging domain of large-scale construction. Her research focuses on two critical, interconnected areas: robust simultaneous localization and mapping (SLAM) for dynamic, unstructured environments, and intelligent path planning on uneven terrain. Li’s major contribution lies in systematically evaluating and advancing LiDAR SLAM algorithms specifically for the chaotic conditions of large public building sites—a setting where traditional methods fail due to point-cloud drift and significant z-axis errors. Her work on an improved A* algorithm directly addresses the inefficiencies of global path planning on uneven ground, reducing prolonged computation times. With her most-cited paper, “Evaluation of LiDAR SLAM algorithms for construction robots,” already garnering 4 citations shortly after publication in 2025, her impact is immediate and growing. By tackling the real-world bottlenecks of autonomous navigation in construction—from safety inspection to autonomous material transport—Li is laying the algorithmic groundwork for the next generation of construction robotics, making her a vital voice in the field of field robotics and civil infrastructure automation.
Research Focus
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