In modern production lines, smaller batches to be produced and higher customization level of a single component bring to higher cost, related especially to setup and preparation of machines. The setup of a milling machine is an operation that requires time and may bring to errors that can be catastrophic. In this Chapter, the ARTool Augmented Reality framework for machine tool operations is presented. The framework permits to write and debug part-code in an augmented environment, to identify quicker misalignments and errors in fixing of new blank material, and to support maintenance operations. The ego-localization of the handheld device that depicts the augmented scene in machine work-area is based upon markers. The library that performs marker identification is brand-new and it is benchmarked throughout the Chapter against a state-of-the-art solution (ARUCO) and a ground truth (multi-stereoscopic motion capture). The Chapter also describes the general information flow and the context that brought to the conception of the ARTool framework, and presents a series of applications developed using the framework.
ARTool: Augmented Reality Human-Machine Interface for Machining Setup and Maintenance / Setti, Amedeo; Bosetti, Paolo; Ragni, Matteo. - STAMPA. - 751:(2018), pp. 131-155. [10.1007/978-3-319-69266-1_7]
ARTool: Augmented Reality Human-Machine Interface for Machining Setup and Maintenance
Setti, Amedeo;Bosetti, Paolo;Ragni, Matteo
2018-01-01
Abstract
In modern production lines, smaller batches to be produced and higher customization level of a single component bring to higher cost, related especially to setup and preparation of machines. The setup of a milling machine is an operation that requires time and may bring to errors that can be catastrophic. In this Chapter, the ARTool Augmented Reality framework for machine tool operations is presented. The framework permits to write and debug part-code in an augmented environment, to identify quicker misalignments and errors in fixing of new blank material, and to support maintenance operations. The ego-localization of the handheld device that depicts the augmented scene in machine work-area is based upon markers. The library that performs marker identification is brand-new and it is benchmarked throughout the Chapter against a state-of-the-art solution (ARUCO) and a ground truth (multi-stereoscopic motion capture). The Chapter also describes the general information flow and the context that brought to the conception of the ARTool framework, and presents a series of applications developed using the framework.File | Dimensione | Formato | |
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