Han Fan

I am PhD student working on SmokeBot project. I have a master degree of Science with major subject Engineering Physics from Chalmers University of Technology in Gothenburg, Sweden. Before I went to the graduate school, I had my undergraduate education in Automation at University of Electronic Science and Technology of China, in Chengdu, P.R. China.

I am interested in a variety of topics in Mobile Robotic Olfaction, including gas sensing, gas discrimination, gas dispersion and distribution modelling, as well as gas source localization. My current work is to address the problem of gas discrimination using e-nose in open environments where unknown interferents are present and environmental conditions are uncontrolled.

Contact

Han Fan

AASS Research Centre
School of Science and Technology
Örebro University
70182 Örebro, Sweden
Phone +46 (0)19 30 30 00
han.fan@oru.se

Publications

Journal Articles

[1]	H. Fan, E. Schaffernicht and A. Lilienthal. Ensemble Learning-Based Approach for Gas Detection Using an Electronic Nose in Robotic Applications. Frontiers in Chemistry, 10, 2022 [ BibTeX \| DiVA \| PDF ]
[2]	Y. Xing, T. A. Vincent, H. Fan, E. Schaffernicht, V. Hernandez Bennetts, A. J. Lilienthal, M. Cole and J. W. Gardner. FireNose on Mobile Robot in Harsh Environments. IEEE Sensors Journal, 19(24):12418-12431, 2019 [ BibTeX \| DiVA ]
[3]	H. Fan, V. Hernandez Bennetts, E. Schaffernicht and A. J. Lilienthal. Towards Gas Discrimination and Mapping in Emergency Response Scenarios Using a Mobile Robot with an Electronic Nose. Sensors, 19(3), 2019 [ BibTeX \| DiVA \| PDF ]
[4]	H. Fan, V. Hernandez Bennetts, E. Schaffernicht and A. Lilienthal. A cluster analysis approach based on exploiting density peaks for gas discrimination with electronic noses in open environments. Sensors and actuators. B, Chemical, 259:183-203, 2018 [ BibTeX \| DiVA \| PDF ]
[5]	J. Monroy, V. Hernandez Bennetts, H. Fan, A. Lilienthal and J. Gonzalez-Jimenez. GADEN : A 3D Gas Dispersion Simulator for Mobile Robot Olfaction in Realistic Environments. Sensors, 17(7):1479-1494, 2017 [ BibTeX \| DiVA \| PDF ]
[6]	V. Hernandez Bennetts, T. P. Kucner, E. Schaffernicht, P. P. Neumann, H. Fan and A. J. Lilienthal. Probabilistic Air Flow Modelling Using Turbulent and Laminar Characteristics for Ground and Aerial Robots. IEEE Robotics and Automation Letters, 2(2):1117-1123, 2017 [ BibTeX \| DiVA ]
[7]	S. Asadi, H. Fan, V. Hernandez Bennetts and A. Lilienthal. Time-dependent gas distribution modelling. Robotics and Autonomous Systems, 96:157-170, 2017 [ BibTeX \| DiVA ]

Refereed Conference and Workshop Articles

[1]	H. Fan, E. Schaffernicht and A. J. Lilienthal. Identification of Gas Mixtures with Few Labels Using Graph Convolutional Networks. In 2024 IEEE International Symposium on Olfaction and Electronic Nose (ISOEN) 2024 [ BibTeX \| DiVA ]
[2]	Y. Zhu, H. Fan, A. Rudenko, M. Magnusson, E. Schaffernicht and A. Lilienthal. LaCE-LHMP : Airflow Modelling-Inspired Long-Term Human Motion Prediction By Enhancing Laminar Characteristics in Human Flow. In 2024 IEEE International Conference on Robotics and Automation (ICRA), pages 11281-11288, 2024 [ BibTeX \| DiVA \| PDF ]
[3]	N. P. Winkler, O. Kotlyar, E. Schaffernicht, H. Fan, H. Matsukura, H. Ishida, P. P. Neumann and A. Lilienthal. Learning From the Past : Sequential Deep Learning for Gas Distribution Mapping. In ROBOT2022 : Fifth Iberian Robotics Conference: Advances in Robotics, Volume 2, 590(590):178-188, 2022 [ BibTeX \| DiVA ]
[4]	H. Fan, D. Jonsson, E. Schaffernicht and A. Lilienthal. Towards Gas Identification in Unknown Mixtures Using an Electronic Nose with One-Class Learning. In 2022 IEEE International Symposium on Olfaction and Electronic Nose (ISOEN) : Proceedings 2022 [ BibTeX \| DiVA ]
[5]	H. Fan, V. Hernandez Bennetts, E. Schaffernicht and A. J. Lilienthal. Semi-supervised Gas Detection Using an Ensemble of One-class Classifiers. In 18th ISOCS/IEEE International Symposium on Olfaction and Electronic Nose (ISOEN) 2019 [ BibTeX \| DiVA \| PDF ]
[6]	H. Fan, M. A. Arain, V. Hernandez Bennetts, E. Schaffernicht and A. J. Lilienthal. Improving Gas Dispersal Simulation For Mobile Robot Olfaction : Using Robot-Created Occupancy Maps And Remote Gas Sensors In The Simulation Loop. In 2017 ISOCS/IEEE International Symposium on Olfaction andElectronic Nose (ISOEN 2017) Proceedings 2017 [ BibTeX \| DiVA ]
[7]	M. A. Arain, H. Fan, V. Hernandez Bennetts, E. Schaffernicht and A. J. Lilienthal. Improving Gas Tomography With Mobile Robots : An Evaluation of Sensing Geometries in Complex Environments. In 2017 ISOCS/IEEE International Symposium on Olfaction andElectronic Nose (ISOEN 2017) Proceedings 2017 [ BibTeX \| DiVA ]
[8]	Y. Xing, T. A. Vincent, M. Cole, J. W. Gardner, H. Fan, V. Hernandez Bennetts, E. Schaffernicht and A. Lilienthal. Mobile robot multi-sensor unit for unsupervised gas discrimination in uncontrolled environments. In IEEE SENSORS 2017 : Conference Proceedings, pages 1691-1693, 2017 [ BibTeX \| DiVA \| PDF ]
[9]	V. Hernandez Bennetts, E. Schaffernicht, A. J. Lilienthal, H. Fan, T. P. Kucner, L. Andersson and A. Johansson. Towards occupational health improvement in foundries through dense dust and pollution monitoring using a complementary approach with mobile and stationary sensing nodes. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 131-136, 2016 [ BibTeX \| DiVA ]
[10]	H. Fan, V. Hernandez Bennetts, E. Schaffernicht and A. J. Lilienthal. Unsupervised gas discrimination in uncontrolled environments by exploiting density peaks. In 2016 IEEE SENSORS 2016 [ BibTeX \| DiVA ]

Theses

[1]	H. Fan. Robot-aided Gas Sensing for Emergency Responses. Örebro University, School of Science and Technology, Ph.D. Thesis, 2022 [ BibTeX \| DiVA ]

Find the complete BibTeX record here.