Papers
5
Total Citations
66
H-Index
4
About
Xun Guo is a pioneering researcher in multi-robot olfaction and indoor environmental robotics, with a focused expertise in locating time-varying pollutant sources within complex, dynamic indoor spaces. Their major contributions lie in experimentally validating bionic swarm intelligence algorithms for 3D source localization, particularly in environments with weak airflow and mechanical ventilation. By bridging the gap between simulation and real-world application, Guo has demonstrated how cooperative multi-robot systems can effectively track and pinpoint particulate matter (PM) sources—a critical challenge given that indoor PM threatens human health, compromises product quality, and poses safety risks. Their work addresses the unpredictable airflow changes and complex PM behavior that make accurate localization difficult. With a growing body of highly cited experimental studies—including a 2021 paper with 25 citations and a 2023 study with 20 citations—Guo’s research has laid the groundwork for practical, deployable robotic solutions. Notably, their 2025 work on bridging simulation-experimentation gaps marks a significant step toward real-world implementation, offering a robust framework for safeguarding indoor environments through intelligent, autonomous robotic cooperation.
Research Focus
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