Kaimin Mao
Papers
1
Total Citations
1
H-Index
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About
Kaimin Mao is a rising researcher in multi-robot systems, with a focus on enabling robust collaboration in challenging, real-world environments. His primary research areas include relative pose estimation, ultra-wideband (UWB) localization, and sensor fusion for autonomous multi-agent systems. Mao’s most notable contribution is his work on anchorless UWB-assisted relative pose estimation, which addresses a critical limitation of traditional camera- or LiDAR-based methods: the need for overlapping fields of view between robots. By eliminating this dependency, his approach significantly enhances the flexibility and reliability of multi-robot coordination in GPS-denied or visually obstructed settings. His 2025 paper, “Overlapping Free: Anchorless UWB-Assisted Relative Pose Estimation for Multi-Robot Systems,” has already garnered early citations, signaling its growing influence in the field. Mao’s work is particularly impactful for applications in search-and-rescue, environmental monitoring, and industrial automation, where robots must operate without constant visual contact. As a young scholar, his innovative solutions are paving the way for more scalable and practical multi-robot systems, making him a promising voice in autonomous robotics research.
Research Focus
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Top Papers
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