Victor Hernandez Bennetts
Welcome to my personal webpage!
I am a machine learning and data science consultant at B3 Commit in Örebro. Before joining B3, I had the pleasure of working as a postdoctoral researcher at the MR&O Lab in Örebro University. I obtained a Ph.D. degree in Computer Science in 2015 and a Masters in Robotics and Intelligent Systems form Örebro University. Machine learning, data science and robotics are my main areas of interests.
Brief CV
I was born in Oaxaca, Mexico in 1980. In 2003, I graduated with a B.Sc. in electronics engineering from the Technological University of the Mixteca (Spanish: Universidad Tecnológica de la Mixteca). From 2004 to 2008 I worked in the automotive industry at CIDED/Delphi E&S as a software engineer and as a systems engineer. In 2008 I moved to Sweden to join the “Robotics and Intelligent Systems” masters programme at Örebro University and in 2010 I presented my masters thesis. In 2015, I obtained a Ph.D. degree in Computer Science from Örebro University. I worked as a postdoc researcher until 2019 at Örebro University and currently, I work for B3 Commit as a machine learning consultant. For more details, please check my LinkedIn profile.
Awards
- KUKA Best Service Robot Paper Award at the 2013 IEEE International Conference on Robotics and Automation (ICRA) for the paper Towards Real-World Gas Distribution Mapping and Leak Localization Using a Mobile Robot with 3D and Remote Gas Sensing Capabilities.
- Award of distinction: Environmental Contribution for the Gasbot project from Clearpath Robotics.
Research Interests
- Machine learning,
- Artificial intelligence,
- Mobile robotics,
- Deep learning
- Sensor systems,
- Artificial Olfaction
Contact
Dr. Victor Hernandez Bennetts
AASS Research Centre
School of Science and Technology
Örebro University
70182 Örebro, Sweden
Room T1215
Phone +46 (0)19 30 36 98
victor.hernandez@oru.se
Publications
Journal Articles
[1] | Sniffing out fugitive methane emissions : autonomous remote gas inspection with a mobile robot. The international journal of robotics research, 40(4-5):782-814, 2021 [ BibTeX | DiVA ] |
[2] | Gas Distribution Mapping and Source Localization Using a 3D Grid of Metal Oxide Semiconductor Sensors. Sensors and actuators. B, Chemical, 304, 2020 [ BibTeX | DiVA ] |
[3] | FireNose on Mobile Robot in Harsh Environments. IEEE Sensors Journal, 19(24):12418-12431, 2019 [ BibTeX | DiVA ] |
[4] | Multi-Domain Airflow Modeling and Ventilation Characterization Using Mobile Robots, Stationary Sensors and Machine Learning. Sensors, 19(5), 2019 [ BibTeX | DiVA | PDF ] |
[5] | Smelling Nano Aerial Vehicle for Gas Source Localization and Mapping. Sensors, 19(3), 2019 [ BibTeX | DiVA | PDF ] |
[6] | Towards Gas Discrimination and Mapping in Emergency Response Scenarios Using a Mobile Robot with an Electronic Nose. Sensors, 19(3), 2019 [ BibTeX | DiVA | PDF ] |
[7] | 3D Gas Distribution with and without Artificial Airflow : An Experimental Study with a Grid of Metal Oxide Semiconductor Gas Sensors. Proceedings, 2(13), 2018 [ BibTeX | DiVA | PDF ] |
[8] | 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 ] |
[9] | Integrating SLAM and gas distribution mapping (SLAM-GDM) for real-time gas source localization. Advanced Robotics, 32(17):903-917, 2018 [ BibTeX | DiVA ] |
[10] | Enabling Flow Awareness for Mobile Robots in Partially Observable Environments. IEEE Robotics and Automation Letters, 2(2):1093-1100, 2017 [ BibTeX | DiVA | PDF ] |
[11] | GADEN : A 3D Gas Dispersion Simulator for Mobile Robot Olfaction in Realistic Environments. Sensors, 17(7):1479-1494, 2017 [ BibTeX | DiVA | PDF ] |
[12] | 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 ] |
[13] | Time-dependent gas distribution modelling. Robotics and Autonomous Systems, 96:157-170, 2017 [ BibTeX | DiVA ] |
[14] | Reconstructing gas distribution maps via an adaptive sparse regularization algorithm. Inverse Problems in Science and Engineering, 24(7):1186-1204, 2016 [ BibTeX | DiVA ] |
[15] | A Probabilistic Gas Patch Path Prediction Approach for Airborne Gas Source Localization in Non-Uniform Wind Fields. Sensor Letters, 12(6-7):1113-1118, 2014 [ BibTeX | DiVA ] |
[16] | Combining Non Selective Gas Sensors on a Mobile Robot for Identification and Mapping of Multiple Chemical Compounds. Sensors, 14(9):17331-17352, 2014 [ BibTeX | DiVA ] |
[17] | Online parameter selection for gas distribution mapping. Sensor Letters, 12(6-7):1147-1151, 2014 [ BibTeX | DiVA ] |
[18] | Gas source localization with a micro-drone using bio-inspired and particle filter-based algorithms. Advanced Robotics, 27(9):725-738, 2013 [ BibTeX | DiVA ] |
[19] | Monitoring of CCS areas using micro unmanned aerial vehicles (MUAVs). Energy Procedia, 37:4182-4190, 2013 [ BibTeX | DiVA ] |
[20] | Mobile robots for localizing gas emission sources on landfill sites : is bio-inspiration the way to go?. Frontiers in Neuroengineering, 4(20):1-12, 2012 [ BibTeX | DiVA ] |
Book Chapters
[1] | Using Chemical Sensors as 'Noses' for Mobile Robots. In Essentials of Machine Olfaction and Taste, pages 219-246, 2016 [ BibTeX | DiVA ] |
Refereed Conference and Workshop Articles
[1] | 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 ] |
[2] | Bayesian Gas Source Localization and Exploration with a Multi-Robot System Using Partial Differential Equation Based Modeling. In 2017 ISOCS/IEEE International Symposium on Olfaction and Electronic Nose (ISOEN 2017) : Proceedings, pages 122-124, 2017 [ BibTeX | DiVA ] |
[3] | Cross-sensitivity of Metal Oxide Gas Sensor to Ambient Temperature and Humidity : Effects on Gas Distribution Mapping. In Proceedings of the 11th Asian Conference on Chemical Sensors, 1808, 2017 [ BibTeX | DiVA ] |
[4] | Exploration and Localization of a Gas Source with MOX Gas Sensorson a Mobile Robot : A Gaussian Regression Bout Amplitude Approach. In 2017 ISOCS/IEEE International Symposium on Olfaction and Electronic Nose (ISOEN 2017) : Proceedings, pages 164-166, 2017 [ BibTeX | DiVA ] |
[5] | 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 ] |
[6] | 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 ] |
[7] | 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 ] |
[8] | Mobile robots for learning spatio-temporal interpolation models in sensor networks - The Echo State map approach : The Echo State map approach. In 2017 IEEE International Conference on Robotics and Automation (ICRA), pages 2659-2665, 2017 [ BibTeX | DiVA | PDF ] |
[9] | From Insects to Micro Air Vehicles : A Comparison of Reactive Plume Tracking Strategies. In Intelligent Autonomous Systems 13, pages 1533-1548, 2016 [ BibTeX | DiVA ] |
[10] | Tell me about dynamics! : Mapping velocity fields from sparse samples with Semi-Wrapped Gaussian Mixture Models. In Robotics : Science and Systems Conference (RSS 2016) 2016 [ BibTeX | DiVA | PDF ] |
[11] | The Right Direction to Smell : Efficient Sensor Planning Strategies for Robot Assisted Gas Tomography. In 2016 IEEE International Conference on Robotics and Automation (ICRA), pages 4275-4281, 2016 [ BibTeX | DiVA | PDF ] |
[12] | 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 ] |
[13] | Unsupervised gas discrimination in uncontrolled environments by exploiting density peaks. In 2016 IEEE SENSORS 2016 [ BibTeX | DiVA ] |
[14] | Bringing Artificial Olfaction and Mobile Robotics Closer Together : An Integrated 3D Gas Dispersion Simulator in ROS. In Proceedings of the 16th International Symposium on Olfaction and Electronic Noses 2015 [ BibTeX | DiVA ] |
[15] | Efficient Measurement Planning for Remote Gas Sensing with Mobile Robots. In 2015 IEEE International Conference on Robotics and Automation (ICRA), pages 3428-3434, 2015 [ BibTeX | DiVA | PDF ] |
[16] | Integrated Simulation of Gas Dispersion and Mobile Sensing Systems. In Workshop on Realistic, Rapid and Repeatable Robot Simulation 2015 [ BibTeX | DiVA ] |
[17] | A Novel Approach for Gas Discrimination in Natural Environments with Open Sampling Systems. In Proceedings of the IEEE Sensors Conference 2014 2014 [ BibTeX | DiVA ] |
[18] | Robot assisted gas tomography : an alternative approach for the detection of fugitive methane emissions. In Workshop on Robot Monitoring 2014 [ BibTeX | DiVA ] |
[19] | A Probabilistic Gas Patch Prediction Approach for Airborne Gas Source Localization in Non-Uniform Wind Fields. In Proceedings of the 15th ISOEN 2013 [ BibTeX | DiVA ] |
[20] | Chemical source localization in real environments integrating chemical concentrations in a probabilistic plume mapping approach. In Proceedings of the 15th International Symposium on Olfaction and Electronic Nose (ISOEN 2013) 2013 [ BibTeX | DiVA ] |
[21] | Online parameter selection for gas distribution mapping. In Proceedings of the ISOEN conference 2013 2013 [ BibTeX | DiVA ] |
[22] | Towards Real-World Gas Distribution Mapping and Leak Localization Using a Mobile Robot with 3D and Remote Gas Sensing Capabilities. In 2013 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), pages 2335-2340, 2013 [ BibTeX | DiVA ] |
[23] | A Least Squares approach for learning gas distribution maps from a set of integral gas concentration measurements obtained with a TDLAS sensor. In Proceedings of the IEEE Sensors Conference, 2012, pages 550-553, 2012 [ BibTeX | DiVA ] |
[24] | Adaptive gas source localization strategies and gas distribution mapping using a gas-sensitive micro-drone. In Proceedings of the 16th ITG / GMA Conference, pages 800-809, 2012 [ BibTeX | DiVA ] |
[25] | Creating true gas concentration maps in presence of multiple heterogeneous gas sources. In Sensors, 2012 IEEE, pages 554-557, 2012 [ BibTeX | DiVA ] |
[26] | Gasbot : A Mobile Robotic Platform for Methane Leak Detection and Emission Monitoring. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Workshop on Robotics for Environmental Monitoring (WREM), Vilamoura, Portugal, October 7-12, 2012 2012 [ BibTeX | DiVA | PDF ] |
[27] | Integration of the humanoid robot Nao inside a smart home : a case study. , pages 35-44, 2010 [ BibTeX | DiVA ] |
Theses
[1] | Mobile robots with in-situ and remote sensors for real world gas distribution modelling. Örebro University, School of Science and Technology, Ph.D. Thesis, 2015 [ BibTeX | DiVA | PDF ] |
Find the complete BibTeX record here.