Integration of ROS and Tecnomatix for the Development of Digital Twins Based Decision-Making Systems for Smart Factories
Autor: | Carolina Saavedra Sueldo, Mariano De Paula, Sebastian A. Villar, Gerardo G. Acosta |
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Jazyk: | Spanish; Castilian |
Rok vydání: | 2021 |
Předmět: |
Scheme (programming language)
Ingenierías y Tecnologías 0209 industrial biotechnology General Computer Science Industry 4.0 Computer science Distributed computing Physical system Integration Autonomous Decision System 02 engineering and technology Digital Twin 020901 industrial engineering & automation Software 0202 electrical engineering electronic engineering information engineering Electrical and Electronic Engineering Information exchange computer.programming_language business.industry ROS Tecnomatix Variety (cybernetics) Robot 020201 artificial intelligence & image processing Software architecture business computer |
Zdroj: | CIC Digital (CICBA) Comisión de Investigaciones Científicas de la Provincia de Buenos Aires instacron:CICBA |
Popis: | Digital twins employs simulation in conjunction with virtual environments and a variety of data coming from different plant equipment and physical systems to continuously update the digital models of the world in a feedback loop scheme to facilitate the decision-making processes. The heterogeneity of existing hardware and software requires the development of software architectures able to deal with the information exchange due to the integration and interaction of several system components and autonomous decision-making systems. In this work we propose the design and construction of a software architecture that integrates a manufacturing process simulator with the well-known robot operating system (ROS-Robot Operating System) to easily interchange information with an autonomous decision-making system. The proposal is tested with the simulator Tecnomatix and the free distribution ROS Melodic. We present an instance of software architecture for a typical complex case study of manufacturing plants and demonstrate its easy integration with an autonomous decision-making system based on the reinforcement- learning paradigm. |
Databáze: | OpenAIRE |
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