Abstract
Modern intelligent manufacturing systems are dynamic environments with the ability to respond and adapt to various internal and external changes that can occur during the manufacturing process. By default, they imply efficient, reliable, and flexible material handling and transportation system, which can be effectively realized by using intelligent mobile robots. In order to achieve locomotion of an intelligent mobile robot that will minimize the usage of space within the manufacturing environment, we propose the development of a new holonomic mobile robot DOMINO (Deep learning-based Omnidirectional Mobile robot with INtelligentcOntrol). 3D model of holonomic mobile robot prototype is developed in CAD software package SolidWorks, and designed parts are produced with additive manufacturing technology. Single board computer Raspberry Pi 4 and microcontroller board Arduino Mega 2560 are used for motion control of the holonomic mobile robot, while control actions are determined by the defined kinematic model of the omnidirectional wheeled mobile robot. The experimental verification shows that the holonomic mobile robot is capable of following a predetermined path while successfully avoiding obstacles within a laboratory model of a manufacturing environment.
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Acknowledgment
This work has been financially supported by the Ministry of Education, Science and Technological Development, through the project “Integrated research in macro, micro, and nano mechanical engineering– Deep learning of intelligent manufacturing systems in production engineering” (contract No. 451-03-9/2021-14/200105), and by the Science Fund of the Republic of Serbia, grant No. 6523109, AI – MISSION 4.0, 2020–2022.
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Đokić, L., Jokić, A., Petrović, M., Miljković, Z. (2021). Design and Development of a Holonomic Mobile Robot for Material Handling and Transportation Tasks. In: Karabegović, I. (eds) New Technologies, Development and Application IV. NT 2021. Lecture Notes in Networks and Systems, vol 233. Springer, Cham. https://doi.org/10.1007/978-3-030-75275-0_78
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DOI: https://doi.org/10.1007/978-3-030-75275-0_78
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