Learning-Based Automation of Robotic Assembly for Smart Manufacturing

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For smart manufacturing, an automated robotic assembly system built upon an autoprogramming environment is necessary to reduce setup time and cost for robots that are engaged in frequent task reassignment. This article presents an approach to the autoprogramming of robotic assembly tasks with minimal human assistance. The approach integrates "robotic learning of assembly tasks from observation" and "robotic embodiment of learned assembly tasks in the form of skills." In the former, robots observe human assembly operations to learn a sequence of assembly tasks, which is formalized into a human assembly script. The latter transforms the human assembly script into a robot assembly script in which a sequence of robot-executable assembly tasks are defined based on action planning supported by workspace modeling and simulated retargeting. The assembly tasks, in the form of the robot assembly script, are then implemented via pretrained robot skills. These skills aim to enable robots to execute difficult tasks that involve inherent uncertainties and variations. We validate the proposed approach by building a prototype of the automated robotic assembly system for a power breaker and an electronic set-top box. The results verify that the proposed automated robotic assembly system is not only feasible but also viable, as it is associated with a dramatic reduction in the human effort required for automating robotic assembly.
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Issue Date
2021-04
Language
English
Article Type
Article
Citation

PROCEEDINGS OF THE IEEE, v.109, no.4, pp.423 - 440

ISSN
0018-9219
DOI
10.1109/JPROC.2021.3063154
URI
http://hdl.handle.net/10203/282799
Appears in Collection
EE-Journal Papers(저널논문)
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