Autonomous Vehicles & Artificial Intelligence Laboratory (AVAILab)

Multidisciplinary laboratory focused on developments and applications within the fields of Mathematical Modelling, Optimisation, Soft & Natural Computing, Self-Organisation & Swarm Robotics, Autonomous Navigation, Computer Vision, and Positioning Systems.

Self-Organising Swarms of Firefighting UAVs

Lead ResearcherDr Mauro S. Innocente
Paolo Grasso
Mohammad Tavakol Sadrabadi
Ioannis Papagiannis
Dr Evangelos Gkanas
Prof Guillermo Rein (and HazeLab)


Fire Propagation Modelling (FireProM)

Self-Organisation for Wildfire Suppression

Multi-Agent Collision Avoidance

Efficiency Enhancement of Class-A Foams with Nanoparticles to Fight Wildfires

Derived Publications

  1. M.T. Sadrabadi, M.S. Innocente, E.I. Gkanas, & I. Papagiannis (2022). Comparison of the effect of one-way and two-way fire-wind coupling on the modelling of wildland fire propagation dynamics. In: Viegas, D.X., Ribeiro, L.M. (eds.) Advances in Forest Fire Research 2022 (115–121). Imprensa da Universidade de Coimbra.
    DOI: 10.14195/978-989-26-2298-9_18.
  2. I. PapagiannisM.S. Innocente, & E.I. Gkanas (2022). Synthesis and Characterisation of Iron Oxide Nanoparticles with Tunable Sizes by Hydrothermal Method. In Materials Science Forum, 1053, 176–181, Trans Tech Publications Ltd.
    DOI: 10.4028/p-0so8ha
  3. P. Grasso, & M.S. Innocente (2022). Stigmergy-based collision-avoidance algorithm for autonomous firefighting drone swarms. Accepted for publication in: Proceedings of fifth International Conference on Computational Vision and Bio Inspired Computing. Advances in Intelligent Systems and Computing, Springer-Nature.
    DOI: 10.1007/978-981-16-9573-5_19
  4. P. Grasso, & M.S. Innocente (2020). Physics-based model of wildfire propagation towards faster-than-real-time simulations. Computers and Mathematics with Applications, 80, 790–808, Elsevier.
    DOI: 10.1016/j.camwa.2020.05.009
  5. M.S. Innocente, & P. Grasso (2019). Self-organising swarms of firefighting drones: Harnessing the power of collective intelligence in decentralised multi-robot systems. Journal of Computational Science, 34, 80–101, Elsevier.
    DOI: 10.1016/j.jocs.2019.04.009
  6. P. Grasso, & M.S. Innocente (2018). A two-dimensional reaction-advection-diffusion model of the spread of fire in wildlands. In Advances in Forest Fire Research 2018 (pp. 334–342). Imprensa da Universidade de Coimbra.
    DOI: 10.14195/978-989-26-16-506_36
  7. M.S. Innocente, & P. Grasso (2018). Swarm of autonomous drones self-organised to fight the spread of wildfires. In Proceedings of the GEOSAFE Workshop on Robust Solutions for Fire Fighting (Vol. 2146), L’Aquila, Italy, 2018. CEUR.
  8. M.S. Innocente, & P. Grasso (2018). Proof-of-Concept Swarm of Self-Organising Drones Aimed at Fighting Wildfires. In Proceedings of the 2017 UK-RAS Conference: ‘Robots Working for and among Us’, pp. 102–105, Bristol, UK, 2017.
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