Modelling multi-rotor UAVs swarm deployment using virtual pheromones.

Area of Science:

• Robotics and Autonomous Systems
• Swarm Intelligence
• Network Engineering

Background:

• Deploying Unmanned Aerial Vehicles (UAVs) for tasks like ad-hoc network creation faces challenges due to sensory, processing, and endurance limitations.
• Existing UAV deployment behaviors often assume specific environmental features, limiting their real-world applicability.

Purpose of the Study:

• To present a new swarm behavior for multi-rotor UAVs.
• To enable adaptable and robust deployment in complex environments without prior information or external signals.
• To facilitate the creation of ad-hoc communication networks for emergency response.

Main Methods:

• Development of a virtual device for quantitative sematectonic stigmergy.
• Microscopic model for UAV deployment and ad-hoc network creation incorporating stigmergy.
• Macroscopic model to predict agent numbers and deployment time.
• Simulation-based experimental analysis to validate models and assess environmental complexity and stigmergy influence.

Main Results:

• The proposed swarm behavior demonstrates high robustness and fault tolerance.
• The models accurately predict the number of UAVs and time required for area coverage.
• Environmental complexity and the stigmergy system significantly influence deployment effectiveness.

Conclusions:

• The virtual stigmergy approach enhances UAV adaptability in complex, unknown environments.
• The developed models provide a reliable framework for planning UAV swarm deployments for emergency tasks.
• This research contributes to the practical application of UAV swarms in creating essential communication infrastructure.