Unmanned Aerial Vehicles Swarm Flocking Architectures: An Overview

Kimathi, Stephen; Lantos, Béla

doi:10.1109/iccc202255925.2022.9922828

Cited by 2 publications

(2 citation statements)

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“…This architecture increases the practical autonomy of the agents and allows the onboard implementation of the controller, and it further reduces delays when transmitting the goal position to the position controllers. The controllers that are involved at the Coordination level are the formation controller, in charge of generating the commands so that the desired formation is achieved, and the tracking control [43], which will command the formation in a coordinated way over the space.…”

Section: Multiagent Control Architecturementioning

confidence: 99%

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Robotic Park: Multi-Agent Platform for Teaching Control and Robotics

et al. 2023

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Multi-agent system research is a hot topic in different application domains. In robotics, multi-agent robot systems (MRS) can realize complex tasks even if the behavior of each individual agent seems simple thanks to the cooperation between them. Although many control algorithms for MRS are proposed, few experimental results are validated on real data, being essential to building new testbeds to conduct MRS research and teaching. Moreover, most existing platforms for experimentation do not offer an overall solution allowing software and hardware design tools. This paper describes the design and operation of Robotic Park, a new indoor experimental platform for research in multi-agent systems. The heterogeneity and flexibility of its configuration are two of its main features. It supports control strategies design and validation of MRS algorithms. Experiences can be carried out in a virtual environment, in a physical environment, or under a hybrid scheme, as digital twins have been developed in Gazebo and Webots. Currently, two types of aerial vehicles, the Crazyflie 2.X and the DJI Tello, are available. It also includes two types of differential mobile robots, the Turtlebot3 and the Khepera IV. Both internal and external positioning systems using different technologies such as Motion Capture or Ultra-WideBand are also available for experiences. All components are connected through ROS2 (Robot Operating System 2) which enables experiences under a centralized, distributed, or hybrid scheme, and different communication strategies can be implemented. A mixed reality experience that addresses the problem of formation control using event-based control illustrates the platform usage.

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Section: Multiagent Control Architecturementioning

confidence: 99%

“…This implementation shows a directed graph. Another strategy is called dominance formation [43], in which a weight is defined for each link, and those edges that connect to the leader have a higher weight. In this case, the leader receives its neighbors' position.…”

Section: Multiagent Control Architecturementioning

confidence: 99%