BEGIN:VCALENDAR PRODID:-//Microsoft Corporation//Outlook 16.0 MIMEDIR//EN VERSION:2.0 METHOD:PUBLISH X-MS-OLK-FORCEINSPECTOROPEN:TRUE BEGIN:VTIMEZONE TZID:W. Europe Standard Time BEGIN:STANDARD DTSTART:16011028T030000 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=10 TZOFFSETFROM:+0200 TZOFFSETTO:+0100 END:STANDARD BEGIN:DAYLIGHT DTSTART:16010325T020000 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=3 TZOFFSETFROM:+0100 TZOFFSETTO:+0200 END:DAYLIGHT END:VTIMEZONE BEGIN:VEVENT CLASS:PUBLIC CREATED:20240305T052236Z DESCRIPTION:Robot-assisted manipulation of flexible components in the produ ction of electric vehicles\nAlper Yaman\, Fraunhofer IPA\n \nFlexible comp onents such as cables and cable harnesses play a key role in the productio n of electric vehicles. However\, they cannot be handled automatically due to a lack of robust processes. The »RoboCable« project researches new A I methods for robot-assisted handling and manipulation of flexible compone nts.\nIn our approach\, robots learn tasks virtually in the simulation env ironment and from real sensor data. The sensors enable autonomous executio n of learned assembly activities. Despite the variability of flexible comp onents and process uncertainties\, new assembly tasks can be learned in si mulation\, allowing existing tasks to continue without interruption\, ther eby minimizing programming and downtime. RoboCable also facilitates the us e of lightweight robots\, alongside traditional industrial robots.\n \n DTEND;TZID="W. Europe Standard Time":20240724T103000 DTSTAMP:20230717T081543Z DTSTART;TZID="W. Europe Standard Time":20240724T100000 LAST-MODIFIED:20240305T052236Z LOCATION:Microsoft Teams PRIORITY:5 SEQUENCE:0 SUMMARY;LANGUAGE=de:»KI-Brekkie« TRANSP:OPAQUE UID:040000008200E00074C5B7101A82E008000000003049569697B8D901000000000000000 0100000001354C25FDD9C814F825189E8166109CD X-ALT-DESC;FMTTYPE=text/html:

Robot-assisted manipulation of flexible components in the p roduction of electric vehicles

Alper Yaman\, Fraunh ofer IPA

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Flexible components such as cables and cable harnesses play a key role in the production of electric vehicles. However\, they cannot be handled automatically due to a lack of robust processes. The »RoboCable« project researches new AI methods for robot-as sisted handling and manipulation of flexible components.
In our approac h\, robots learn tasks virtually in the simulation environment and from re al sensor data. The sensors enable autonomous execution of learned assembl y activities. Despite the variability of flexible components and process u ncertainties\, new assembly tasks can be learned in simulation\, allowing existing tasks to continue without interruption\, thereby minimizing progr amming and downtime. RoboCable also facilitates the use of lightweight robots\, alongside traditional industrial robots.

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