Qing‐Hao Meng
Papers
65
Total Citations
1,069
H-Index
16
About
Qing-Hao Meng is a prominent robotics researcher whose work sits at the intersection of mobile robotics, olfactory sensing, and autonomous navigation. Based at Tianjin University, Meng has devoted much of his career to the challenging problem of robot odor source localization (OSL) — developing intelligent systems capable of detecting and tracing hazardous chemical releases in complex, real-world environments. His 2011 paper applying particle filter algorithms to outdoor odor localization has garnered over 200 citations, establishing foundational methodology in the field, while his 2021 review paper on OSL progress reflects his sustained leadership across more than a decade of rapid development. Meng has pioneered multi-robot approaches, adapting ant colony metaphors and particle swarm optimization to enable collective chemical plume tracing in dynamic airflow conditions. Beyond olfaction, his contributions extend to mobile robot localization using adaptive Kalman filtering and sonar-based sensing, where he also addressed the persistent engineering challenge of ultrasonic crosstalk through novel pulse modulation techniques. More recently, he has explored gas-sensitive UAV platforms through aerodynamic olfactory modeling. With hundreds of citations across diverse robotics subfields, Meng's work provides both theoretical grounding and practical tools for emergency response, environmental monitoring, and autonomous robot sensing.
Research Focus
Key Achievements
Top Papers
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- 2Recent Progress and Trend of Robot Odor Source Localization101 citations · 2021
- 3Adapting an Ant Colony Metaphor for Multi-Robot Chemical Plume Tracing56 citations · 2012
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