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1School of Aerospace, Transport and Manufacturing, Cranfield University, UK
2Centre for Structures, Assembly and Intelligent Automation, School of Aerospace, Transport and Manufacturing, Cranfield University, UK
*Corresponding author: Seemal Asif, Centre for Structures, Assembly and Intelligent Automation, School of Aerospace, Transport and Manufacturing, Cranfield University, UK
Submission: September 27, 2021; Published: October 11, 2021
Volume2 Issue3
Drones are also known as UAVs are originally designed for military purposes. With the technological advances, they can be seen in most of the aspects of life from filming to logistics. The increased use of drones made it sometimes essential to form a collaboration between them to perform the task efficiently in a defined process. This paper investigates the use of a combined centralised and decentralised architecture for the collaborative operation of drones in a parts delivery scenario to enable and expedite the operation of the factories of the future. The centralised and decentralised approaches were extensively researched, with experimentation being undertaken to determine the appropriateness of each approach for this use-case. Decentralised control was utilised to remove the need for excessive communication during the operation of the drones, resulting in smoother operations. Initial results suggested that the decentralised approach is more appropriate for this use-case. The individual functionalities necessary for the implementation of a decentralised architecture were proven and assessed, determining that a combination of multiple individual functionalities, namely VSLAM, dynamic collision avoidance and object tracking, would give an appropriate solution for use in an industrial setting. A final architecture for the parts delivery system was proposed for future work, using a combined centralised and decentralised approach to combat the limitations inherent in each architecture.
Keywords: IoRT; Swarm robotics; Centralized; Decentralized; Autonomy; Intralogistics; Monocular depth estimation; Human-robot interaction; Industry 4.0; UAV
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