Papers
23
Total Citations
255
H-Index
9
About
Maohai Li is a robotics researcher whose work spans mobile robot autonomy, localization, mapping, and intelligent logistics systems. Over more than a decade of prolific research, Li has made foundational contributions to the fields of simultaneous localization and mapping (SLAM), omnidirectional vision-based navigation, and autonomous warehouse robotics. His early work pioneered the application of Rao-Blackwellized Particle Filters combined with Unscented Kalman Filters for monocular vision-based SLAM, establishing robust probabilistic frameworks for robots navigating unknown indoor environments — work that has collectively garnered dozens of citations across multiple publications. His research on omnidirectional vision-based hierarchical localization and topological navigation (40 and 26 citations respectively) demonstrated scalable, real-world solutions for mobile robot autonomy. Li later translated these theoretical foundations into practical industrial systems, designing automated guided logistics robots capable of transporting pallets weighing up to 1,000 kg, and pioneering an innovative master-slave parallel robot architecture for smart factory applications. His multi-robot cooperative pursuit work further showcases his breadth in swarm intelligence and data-driven coordination. With over 200 cumulative citations, Li's research bridges fundamental algorithms and real-world deployment in intelligent robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2An automated guided logistics robot for pallet transportation31 citations · 2020
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- 4
- 5Multi-robot Cooperative Pursuit Based on Association Rule Data Mining18 citations · 2009
- 6
- 7Coevolution Based Adaptive Monte Carlo Localization15 citations · 2005
- 8A novel method for mobile robot simultaneous localization and mapping14 citations · 2006
- 9
- 10Active Mobile Robot Simultaneous Localization and Mapping9 citations · 2006