We will pursue a concentrated research effort towards automating challenging and DDD (dull, dangerous, dirty) tasks concerning the handling of raw material in production lines currently executed manually. We will focus on artificial intelligence inspired vision based approaches to categorize and segment the raw material and its geometry to subsequently define (again through AI) optimal handling/grasping poses for the automation machinery. We seek to automate existing infrastructure in a versatile and cost effective way. Thus, we will investigate in retrofittable sensors and robust control strategies for seamless and cost efficient upgrading/retrofitting/automating existing infrastructure. As a specific application scenario and immediate benefit to Austrian’s industry, we will tackle the problem of autonomously grasping logs to be placed from the truck to the processing machinery of a forestry company.
|Effective start/end date||1/04/18 → 31/03/21|
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