Drone Swarms as Networked Control Systems by Integration of Networking and Computing

Area of Science:

• Robotics and Automation
• Networked Systems
• Control Theory

Background:

• Drone swarms exhibit cooperative behavior, but automating their control is complex due to dynamic constraints.
• Existing literature lacks comprehensive reviews on designing drone swarms specifically as Networked Control Systems (NCS).

Purpose of the Study:

• To provide an overview of developing self-organized drone swarms as NCS.
• To analyze the integration of networking and computational systems for improved drone swarm performance.
• To identify design choices and open research challenges in this domain.

Main Methods:

• Literature analysis to identify research gaps.
• Conceptual framework for integrating networking and computational systems in drone swarms.
• Analysis of component properties and their synergistic effects.

Main Results:

• Drone swarms can be effectively modeled as NCS by tightly integrating networking and computational systems.
• This integration supports essential control functions: data exchange, decision-making, and command distribution.
• The review highlights specific properties of networking and computational components for NCS drone swarms.

Conclusions:

• A unified approach to drone swarm design as NCS is feasible and beneficial.
• Further research is needed to address identified open challenges in integrating network and computing for drone swarms.
• This work lays the groundwork for future advancements in autonomous, cooperative drone systems.