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FlockAI

An AI Enabled Framework to Boost Drone Swarm Autonomy

Welcome to the FlockAI project website!

The aim of the FlockAI project is to deliver a framework capable of enabling Machine Learning and its applications to drone technology for handling time-critical missions (e.g., search and rescue missions). Specifically, FlockAI will advance the current research plain by developing innovative AI-enabled self-adaptive algorithms to ease energy consumption and improve data delivery timeliness in drone swarms. To achieve these goals, the FlockAI project will explore the use of various power-efficient machine learning models for dynamically adjusting, in place, the data sensing and routing of data over drone swarms while maintaining mission requirements. The methods delivered by the project will be placed in a modular and reusable framework for drone swarm operation.

Project Objectives

Current Work

The FlockAI research team is currently working on designing and developing a framework that will enable researchers to rapidly test advanced AI models for drone technology. Users of our benchmarking framework will be able to rapidly provision -reproducable- emulated testbeds for AI experimentation without the need of knowing complex internals of drone technology or emulation frameworks.

Stay tuned for the first release of our benchmarking suite that will run on top of the open and popular webots emulator!

flockai-webots-1 flockai-webots-2 flockai-webots-3

The Team

Principle Investigator

Dr. Demetris Trihinas (Geo-Distributed Data Processing)

Researchers

Dr. Michalis Agathocleous (Deep Learning) Mr. Karlen Avogian (Cloud DevOps)

Consulting Research Team

Prof. Athena Stassopoulou (Swarm Intelligence) Dr. Ioannis Katakis (Data Mining/Machine Learning) Dr. Ioannis Kyriakides (Signal Processing)

Contact

For more information about the project and our current work, please contact the project principle investigator, Dr. Demetris Trihinas at trihinas.d {at} unic.ac.cy

Acknowledgement

This project is run by the Artificial Intelligence Laboratory (ailab) and is co-funded by the University of Nicosia Seed Grant Scheme (2020-2022).