Contact Patrick Geragersian
Areas of expertise
- Aeronautical Systems
- Autonomous Systems
Background
Patrick Geragersian is a researcher at Cranfield University, bringing extensive experience in mechanical engineering and digital solutions to the role. He previously worked as part of the decommissioning team at Atkins (SNC-Lavlin), where he was involved in developing cutting-edge VR and AR stakeholder engagement tools, as well as automating engineering tasks. With a Master's degree in Aerospace Engineering from the University of Manchester, Patrick has a strong foundation in his field.
At Cranfield University, Patrick is currently focusing his research on alternative PNT (position, navigation, and timing) technologies and navigation via machine learning fusion. This involves exploring new methods to enhance the accuracy and reliability of unmanned aerial vehicle navigation, specifically through the integration of alternative PNT sources and machine learning algorithms. Through this research, Patrick is seeking to advance the field of UAV navigation and provide new solutions to meet the evolving needs of this rapidly growing industry.
Current activities
His current research involves the use of GRUs (Gated Recurrent Units) to mitigate the effects of multipath, and the use of Bayesian-LSTMs to understand uncertainty in fused positioning estimates. Through this work, Patrick is exploring new methods to enhance the accuracy and reliability of UAV navigation, and furthering our understanding of the limitations and potential of advanced machine learning algorithms in this field.
Clients
NHS (National Health Service)
Spirent Communications Plc
ESA (European Space Agency)
NCA (National Crime Agency)
Publications
Articles In Journals
Conference Papers
- Geragersian P, Petrunin I, Guo W & Grech R. (2023). Uncertainty-based Sensor Fusion Architecture using Bayesian-LSTM Neural Network
- Negru SA, Geragersian P, Petrunin I, Zolotas A & Grech R. (2023). GNSS/INS/VO fusion using Gated Recurrent Unit in GNSS denied environments
- Ozdemir YE, Isik OK, Geragersian P, Petrunin I, Grech R, .... (2023). Performance Enhancement of Low-Cost INS/GNSS Navigation System Operating in Urban Environments
- Geragersian P, Petrunin I, Guo W & Grech R. (2023). A Hybrid Deep Learning Approach for Robust Multi-Sensor GNSS/INS/VO Fusion in Urban Canyons
- Negru SA, Geragersian P, Petrunin I, Grech R & Buesnel G. (2023). Realism-Oriented Design, Verification, and Validation of Novel Robust Navigation Solutions
- Geragersian P, Petrunin I, Guo W & Grech R. (2022). An INS/GNSS fusion architecture in GNSS denied environment using gated recurrent unit
- Geragersian P, Petrunin I, Guo W & Grech R. (2022). Multipath Detection from GNSS Observables Using Gated Recurrent Unit