Browsing by Author "Petrunin, Ivan"

Browsing by Author "Petrunin, Ivan"

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  • AFJPDA: a multiclass multi-object tracking with appearance feature-aided joint probabilistic data association 
    Kim, Sukkeun; Petrunin, Ivan; Shin, Hyo-Sang (AIAA, 2024-01-02)
    This study addresses a multiclass multi-object tracking problem in consideration of clutters in the environment. To alleviate issues with clutters, we propose the appearance feature-aided joint probabilistic data association ...
  • Analysis of synchronization in distributed avionics systems based on time-triggered ethernet 
    Tariq, Nahman; Petrunin, Ivan; Al-Rubaye, Saba (IEEE, 2021-11-15)
    Significant developments are made in unmanned aerial vehicles (UAVs) and in avionics, where messages sent in the network with critical Time play a vital role. Several studies in Time-Triggered Ethernet have been carried ...
  • Analysis of wireless connectivity applications at airport surface 
    Ayub, Shahid; Petrunin, Ivan; Tsourdos, Antonios; Xu, Zhengjia (IEEE, 2020-04-30)
    The main objective of the current work is to carry out the research to explore the potential wireless communication technologies that can be used during a flight operation at the airport surface for current and potential ...
  • Application of fibre optic sensing systems to measure rotor blade structural dynamics 
    Weber, Simone; Kissinger, Thomas; Chehura, Edmond; Staines, Stephen; Barrington, James; Mullaney, Kevin; Fragonara, Luca Zanotti; Petrunin, Ivan; James, Stephen; Lone, Mudassir; Tatam, Ralph P. (Elsevier, 2021-03-09)
    This paper compares two fibre optic sensing techniques for vibration characterisation: (a) optical fibre Bragg grating (FBG) strain gauges and (b) a novel direct fibre optic shape sensing (DFOSS) approach based on differential ...
  • Assuring safe and efficient operation of UAV using explainable machine learning 
    Alharbi, Abdulrahman; Petrunin, Ivan; Panagiotakopoulos, Dimitrios (MDPI, 2023-05-19)
    The accurate estimation of airspace capacity in unmanned traffic management (UTM) operations is critical for a safe, efficient, and equitable allocation of airspace system resources. While conventional approaches for ...
  • Autonomous inspection and repair of aircraft composite structures 
    Kostopoulos, Vassilis; Psarras, Spyridon; Loutas, Theodoros; Sotiriadis, George; Gray, Iain; Padiyar M, Janardhan; Petrunin, Ivan; Raposo Gaudencio Campos, Joao; Zanotti Fragonara, Luca; Tzitzilonis, Vasileios; Dassios, Konstantinos; Exarchos, Dimitrios; Andrikopoulos, George; Nikolakopoulos, George (Elsevier, 2018-11-23)
    This paper deals with the development of an innovative approach for inspection and repair of damage in aeronautical composites that took place in the first two years of the H2020 CompInnova project which. The aim is a newly ...
  • Autonomous navigation with taxiway crossings identification using camera vision and airport map 
    Delezenne, Quentin; Petrunin, Ivan; Xu, Zhengjia; Neptune, Jonathan; Bleakley, Timothy (AIAA, 2024-01-04)
    With increasing demands of unmanned aerial vehicle (UAV) operations envisioned for the future of aviation, the number of pilots will be much lower than the number of drones, necessitating an increased level of autonomy in ...
  • Bladesense – a novel approach for measuring dynamic helicopter rotor blade deformation 
    Weber, Simone; Southgate, Dominic; Mullaney, Kevin; James, Stephen; Rutherford, Robert; Sharma, Anuj; Lone, Mudassir; Kissinger, Thomas; Chehura, Edmond; Staines, Stephen; Pekmezci, Huseyin; Fragonara, Luca Zanotti; Petrunin, Ivan; Williams, Dan; Moulitsas, Irene; Cooke, Alastair; Rosales, Waldo; Tatam, Ralph P.; Morrish, Peter; Fairhurst, Mark; Atack, Richard; Bailey, Gordon; Morley, Stuart (European Rotorcraft Forum, 2018-12-31)
    Technologies that allow accurate measurement of rotorblade dynamics can impact almost all areas of the rotorcraft sector; ranging from maintenance all the way to blade design. The BladeSense project initiated in 2016 aims ...
  • Cognitive communication scheme for unmanned aerial vehicle operation 
    Xu, Zhengjia; Petrunin, Ivan; Tsourdos, Antonios; Sabyasachi, Mondal; Williamson, Alex (IEEE, 2020-02-17)
    An intelligent and agile wireless communication scheme is a key factor in provision of efficient air-to-ground (A2G) communication for unmanned aerial vehicles (UAVs) operations. For this purpose we review and propose an ...
  • Combination and selection of machine learning algorithms in GNSS architecture design for concurrent executions with HIL testing 
    Xu, Zhengjia; Petrunin, Ivan; Tsourdos, Antonios; Grech, Raphael; Peltola, Pekka; Tiwari, Smita (IEEE, 2023-11-10)
    As machine learning (ML) continuing to gain popularity, ML-assisted Global Navigation Satellite System (GNSS) receivers facilitate the performance of Autonomous Systems (AS) navigation solutions. However, selections of ML ...
  • A composite learning approach for multiple fault diagnosis in gears 
    Inyang, Udeme Ibanga; Petrunin, Ivan; Jennions, Ian (SAGE, 2022-11-05)
    A major part of Prognostic and Health Management of rotating machines is dedicated to diagnosis operations. This makes early and accurate diagnosis of single and multiple faults an economically important requirement of ...
  • Deep learning architecture for UAV traffic-density prediction 
    Alharbi, Abdulrahman; Petrunin, Ivan; Panagiotakopoulos, Dimitrios (MDPI, 2023-01-22)
    The research community has paid great attention to the prediction of air traffic flows. Nonetheless, research examining the prediction of air traffic patterns for unmanned aircraft traffic management (UTM) is relatively ...
  • Design and hardware-in-the-loop evaluation of a time dissemination framework for drone operations in urban environments 
    Negru, Sorin Andrei; Petrunin, Ivan; Guo, Weisi; Tsourdos, Antonios (IEEE, 2023-11-10)
    With the advent of UAVs (Unmanned Aerial Vehicles) several companies started to offer services, in urban, semi-urban, and rural regions. Although GNSS (Global Navigation Satellite System) can disseminate time information ...
  • Detect and avoid considerations for safe sUAS operations in urban environments 
    Celdran Martinez, Victor; Ince, Bilkan; Kumar Selvam, Praveen; Petrunin, Ivan; Seo, Min-Guk; Anastassacos, Edward; Royall, Paul G.; Cole, Adrian; Tsourdos, Antonios; Knorr, Sebastian (IEEE, 2021-11-15)
    Operations involving small Unmanned Aerial Systems (sUAS) in urban environments are occurring ever more frequently as recognized applications gain acceptance, and new use cases emerge, such as urban air mobility, medical ...
  • Developing drone experimentation facility: progress, challenges and cUAS consideration 
    Panagiotakopoulos, Dimitrios; Williamson, Alex; Petrunin, Ivan; Harman, Stephen; Quilter, Tim; Williams-Wynn, Ian; Goudie, Gavin; Watson, Neil; Vernall, Phil; Reid, Jonathan; Puscius, Eimantas; Cole, Adrian; Tsourdos, Antonios (IEEE, 2021-07-02)
    The operation of Unmanned Aerial Systems (UAS) is widely recognised to be limited globally by challenges associated with gaining regulatory approval for flight Beyond Visual Line of Sight (BVLOS) from the UAS Remote Pilot. ...
  • Diagnosis of multiple faults in rotating machinery using ensemble learning 
    Inyang, Udeme Ibanga; Petrunin, Ivan; Jennions, Ian (MDPI, 2023-01-15)
    Fault diagnosis of rotating machines is an important task to prevent machinery downtime, and provide verifiable support for condition-based maintenance (CBM) decision-making. Deep learning-enabled fault diagnosis operations ...
  • Distributed trajectory management for urban air mobility operations with ground-based edge intelligence 
    Huang, Cheng; Petrunin, Ivan; Tsourdos, Antonios (IEEE, 2023-11-10)
    Trajectory management is a critical undertaking in urban air mobility (UAM) to ensure safe, secure, and efficient operations. Cooperative targets have the capability to report their information while managing non-cooperative ...
  • Drone model classification using convolutional neural network trained on synthetic data 
    Wisniewski, Mariusz; Rana, Zeeshan A.; Petrunin, Ivan (MDPI, 2022-08-12)
    We present a convolutional neural network (CNN) that identifies drone models in real-life videos. The neural network is trained on synthetic images and tested on a real-life dataset of drone videos. To create the training ...
  • Drone model identification by convolutional neural network from video stream 
    Wisniewski, Mariusz; Rana, Zeeshan A.; Petrunin, Ivan (IEEE, 2021-11-15)
    We present a convolutional neural network model that correctly identifies drone models in real-life video streams of flying drones. To achieve this, we show a method of generating synthetic drone images. To create a diverse ...
  • Dynamic graph propagation for performance-based tactical conflict resolution in urban air mobility 
    Huang, Huang; Petrunin, Ivan; Tsourdos, Antonios (IEEE, 2023-06-26)
    Tactical conflict management is a crucial issue for time-sensitive urban air mobility (UAM) operations, considering safety, security, and efficiency factors. To achieve real-time conflict resolution in structural UAM ...