Event-Triggered Image Moments Predictive Control for Tracking Evolving Features Using UAVs

Sotirios N. Aspragkathos, George C. Karras, Kostas J. Kyriakopoulos

Research output: Contribution to journalArticlepeer-review


This paper presents a novel approach for tracking deformable contour targets using Unmanned Aerial Vehicles (UAVs). The proposed scheme combines image moments descriptor and Event-Triggered (ET) Nonlinear Model Predictive Control (NMPC) for efficient and accurate tracking. The deformable contour model allows adaptation to the evolving target's shape, while the proposed event-triggered scheme achieves improved computational efficiency and extended flight duration while generating new control sequences for the UAV. Real-world experimental validation as well as a comparative simulation performance analysis validate the scheme, showcasing its robustness in handling complex scenarios. This approach holds promise for various applications, such as surveillance and autonomous navigation.

Original languageEnglish (US)
Pages (from-to)1019-1026
Number of pages8
JournalIEEE Robotics and Automation Letters
Issue number2
StatePublished - Feb 1 2024


  • Visual servoing
  • aerial systems: Perception and autonomy
  • autonomous agents

ASJC Scopus subject areas

  • Mechanical Engineering
  • Control and Optimization
  • Artificial Intelligence
  • Human-Computer Interaction
  • Control and Systems Engineering
  • Computer Vision and Pattern Recognition
  • Biomedical Engineering
  • Computer Science Applications


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