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Jan Hodapp
Development of an Intuition Based Programming System for Collaborative Robots in Industrial Environments
The development of Industry 4.0 and the ongoing digitalization demand faster adoption and implementation of information and communication technologies from automotive companies.
This work explores the current supply of high level information technologies like object detection with convolutional neural networks or big data analytics for irregularity recognition. Even major production companies face challenges in implementing these technologies. Therefore a concept is proposed to introduce them into production by utilizing skill based programming for sensitive light weight robots.
Skill based programming uses abstraction layers to divide the work of a robot programmer and a shop floor worker in such a way that the programmer generates universal, selfasserting and extractable elements, which the unskilled worker can utilize to teach a cooperative robot to do production tasks. With that, the programmer can concentrate on the complicated intrinsics of his element, while the shop floor worker can use his knowledge of the production to perform implementation, operation and service. This work extends the idea of skill based programming onto high level information technologies. The goal is to empower the worker, programmer and engineer to introduce new technologies into car production resistance free and effortless.
The technologies are integrated into two smart production assistants, collaborative robots developed for working with and being programmed by shop floor workers in MercedesBenz AG car production facilities. They are tested and evaluated for their usefulness and how well they conform to the required flexibility and complexity and also how well they distribute competencies in the various stages of their development and operation.
This work explores the current supply of high level information technologies like object detection with convolutional neural networks or big data analytics for irregularity recognition. Even major production companies face challenges in implementing these technologies. Therefore a concept is proposed to introduce them into production by utilizing skill based programming for sensitive light weight robots.
Skill based programming uses abstraction layers to divide the work of a robot programmer and a shop floor worker in such a way that the programmer generates universal, selfasserting and extractable elements, which the unskilled worker can utilize to teach a cooperative robot to do production tasks. With that, the programmer can concentrate on the complicated intrinsics of his element, while the shop floor worker can use his knowledge of the production to perform implementation, operation and service. This work extends the idea of skill based programming onto high level information technologies. The goal is to empower the worker, programmer and engineer to introduce new technologies into car production resistance free and effortless.
The technologies are integrated into two smart production assistants, collaborative robots developed for working with and being programmed by shop floor workers in MercedesBenz AG car production facilities. They are tested and evaluated for their usefulness and how well they conform to the required flexibility and complexity and also how well they distribute competencies in the various stages of their development and operation.
Schlagwörter: Collaborative Robot Machine Learning; Industrial Environments; Intuition Based Programming System
Berichte aus dem Lehrstuhl Automatisierungstechnik BTU Cottbus-Senftenberg
Herausgegeben von Prof. Dr.-Ing. Ulrich Berger, Cottbus
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DOI 10.2370/9783844072747
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