Lei Mo
Papers
1
Total Citations
1
H-Index
1
About
Lei Mo is a leading researcher in multi-robot systems and autonomous navigation, with a primary focus on collaborative coverage path planning. His most influential work introduces an improved Boustrophedon Cellular Decomposition (BCD) segmentation method that enables multiple robots to efficiently and cooperatively cover unknown indoor environments. By optimizing task allocation and reducing redundant movement, Mo’s approach significantly enhances the scalability and computational efficiency of multi-robot teams—a critical advancement for applications in search-and-rescue, warehouse logistics, and environmental monitoring. His 2025 paper on this topic has already garnered early citations, reflecting growing interest in his lightweight, storage-efficient algorithms. Mo’s contributions stand out for bridging theoretical decomposition techniques with practical, real-time deployment constraints. His work is widely recognized for pushing the boundaries of collaborative task planning, offering a robust foundation for future research in swarm robotics and autonomous exploration.
Research Focus
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Top Papers
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