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Autor(en):
V. Srinivasan, N. Markusheska, J.-N. Walther, A. Gindorf, C. Hesse, J. Biedermann, F. Meller, B. Nagel
Zusammenfassung:
Envisioning advance assembly concepts in Aircraft manufacturing are essential for sustaining the competition and acquiring customers. In this paper we focus ourselves on describing an approach that offers adaptable process flow, reliable assembling methodology that provides faster cycle time along with safety to human workers. Further we also introduce the methodologies to program robot control from different sources which could be of interest to the Aerospace manufacturers. The process planning associated with deployment of robots and communication between the robots using external sensors are described here. Based on existing assembly model for cabin, the initial assembly instructions are written with Ontology. Time consuming activities during such assembly work are identified and interactions are reframed such that the overall assembly time is optimized. This is achieved by collecting and storing the meta-data of the robot motion which may describe the different process times, and associated robot motions. Feasibility on preempting the failure through live visualization of robot data (such as joint current, joint temperature) is studied along with analyzing and improving process by visualizing robot motions in Blender.
Veranstaltung:
Deutscher Luft- und Raumfahrtkongress 2020
Verlag, Ort:
Deutsche Gesellschaft für Luft- und Raumfahrt - Lilienthal-Oberth e.V., Bonn, 2020
Medientyp:
Conference Paper
Sprache:
englisch
Format:
21,0 x 29,7 cm, 7 Seiten
URN:
urn:nbn:de:101:1-2020121614335680013482
DOI:
10.25967/530315
Stichworte zum Inhalt:
Autonomous Robot, Cabin, Ontology, Safety, Image Processing, Customization
Verfügbarkeit:
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Kommentar:
Zitierform:
Srinivasan, V.; Markusheska, N.; et al. (2020): Autonomous Control of an Industrial Robot based on Formalized Process Description for Cabin Assembly. Deutsche Gesellschaft für Luft- und Raumfahrt - Lilienthal-Oberth e.V.. (Text). https://doi.org/10.25967/530315. urn:nbn:de:101:1-2020121614335680013482.
Veröffentlicht am:
16.12.2020