Papers
21
Total Citations
397
H-Index
10
About
Ji-Gong Li is a robotics researcher specializing in mobile robot olfaction, with a particular focus on odor source localization, plume tracing, and chemical source searching in complex real-world environments. His work sits at the intersection of autonomous robotics, computational intelligence, and environmental sensing, addressing the challenging problem of equipping mobile robots with the ability to detect, track, and pinpoint chemical or odor sources in dynamic airflow conditions—both indoors and outdoors. Li's most influential contribution is his 2011 paper on particle filter-based odor source localization in outdoor airflow environments, which has garnered over 200 citations and established him as a leading voice in the field. He has advanced multi-robot coordination strategies through his Probability-PSO algorithms and developed innovative path planning methods, including the estimation-based route planning (ERP) framework validated through real-world field experiments. His biologically inspired "Surge-S" algorithm and work with Dempster-Shafer theory for multi-source mapping further demonstrate the breadth and creativity of his approach. Collectively, Li's research has shaped foundational methodologies for robotic chemical sensing, with applications ranging from environmental monitoring to search-and-rescue operations, making his body of work essential reading for researchers exploring autonomous sensory robotics.
Research Focus
Key Achievements
Top Papers
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- 5Mobile Robot based Odor Path Estimation via Dynamic Window Approach14 citations · 2008
- 6Mobile robot based odor source localization via particle filter13 citations · 2009
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