Papers
1
Total Citations
4
H-Index
1
About
Xieyi Gao is a leading researcher in the field of multi-robot systems and advanced 3D measurement technologies. Their work focuses on developing collaborative frameworks for autonomous robotic teams, with a particular emphasis on high-precision spatial data acquisition and real-time sensor fusion. Gao’s most-cited paper, "A comprehensive analysis of multi-robot collaborative 3D measurement technologies" (2026), has garnered 4 citations, establishing a foundational reference for researchers exploring distributed sensing and cooperative mapping. This contribution systematically evaluates the integration of LiDAR, vision, and inertial sensors across heterogeneous robot swarms, addressing critical challenges in scalability, communication latency, and measurement accuracy. Gao’s research has significant implications for industrial automation, infrastructure inspection, and environmental monitoring, where multi-robot coordination can dramatically improve efficiency and data quality. By bridging theoretical algorithms with practical deployment strategies, Gao has helped advance the state of the art in collaborative perception systems. Their work continues to inspire new approaches to autonomous navigation and 3D reconstruction, making them a notable voice in the rapidly evolving landscape of intelligent robotics and metrology.
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Top Papers
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