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Remotely Controlled Robot Swarms: A Structural Analysis and Model for Structural Optimization

Institute of Vehicles and Construction Machinery Engineering, Faculty of Automotive and Construction Machinery Engineering, Warsaw University of Technology, Politechniki 1, 00-661 Warsaw, Poland
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Academic Editor: Paola Pellegrini
Appl. Sci. 2021, 11(18), 8539; https://doi.org/10.3390/app11188539
Received: 23 July 2021 / Revised: 9 September 2021 / Accepted: 12 September 2021 / Published: 14 September 2021
(This article belongs to the Section Robotics and Automation)
In this paper, the authors analyse the structure of robot swarms. Drive, communication, and artificial intelligence technologies have reached a level where the inspiration of the animal world has become very useful for the development of systems of which people have dreamed for centuries. A short introduction describes the need for and expectations of autonomous robots and vehicles. A classification of swarm structures is based on animals such as bees or ants. Two main types of swarms are recognized: structural (master–slaves) and non-structural. The operator controls both of them remotely. The swarm structure has a great influence on the structure of single robots. A computer model with an object programming definition was worked out, and a simulation of the presented swarm structure is provided. The results are described in the paper. View Full-Text
Keywords: swarm robots; remote control; autonomous machines swarm robots; remote control; autonomous machines
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MDPI and ACS Style

Deda, J.; Mirosław, T. Remotely Controlled Robot Swarms: A Structural Analysis and Model for Structural Optimization. Appl. Sci. 2021, 11, 8539. https://doi.org/10.3390/app11188539

AMA Style

Deda J, Mirosław T. Remotely Controlled Robot Swarms: A Structural Analysis and Model for Structural Optimization. Applied Sciences. 2021; 11(18):8539. https://doi.org/10.3390/app11188539

Chicago/Turabian Style

Deda, Jakub, and Tomasz Mirosław. 2021. "Remotely Controlled Robot Swarms: A Structural Analysis and Model for Structural Optimization" Applied Sciences 11, no. 18: 8539. https://doi.org/10.3390/app11188539

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