Processing Time Optimization for Robot Applications

Muradi M, Wanka R (2020)

Publication Language: English

Publication Type: Conference contribution, Original article

Publication year: 2020

Pages Range: 161-169

Conference Proceedings Title: Proc. 6th International Conference on Control, Automation and Robotics (ICCAR)

Event location: Singapore SG

ISBN: 978-1-7281-6139-6

DOI: 10.1109/ICCAR49639.2020.9108089

Abstract

This research work includes the use of heuristic algorithms to automatically generate processing time optimized robot programs for manufacturing processes in the automotive industry. For this, we've implemented a genetic algorithm with multi-parent recombination and adjacency-based crossover. A reallocation mutation is also introduced to optimize the load balancing by classifying tasks into common and fixed tasks depending on their location relative to the robots' workspace. The heuristic is compared to an exact solver by applying it to a test problem. Lastly, the methodology is also applied to a real business problem in the area of vehicle sealing.

Authors with CRIS profile

Murad Muradi Professur für Informatik (Effiziente Algorithmen und Kombinatorische Optimierung) Rolf Wanka Professur für Informatik (Effiziente Algorithmen und Kombinatorische Optimierung)

Related research project(s)

Algorithmen für kombinatorische Probleme (AlKoP) March 13, 2017 - March 13, 2020

How to cite

APA:

Muradi, M., & Wanka, R. (2020). Processing Time Optimization for Robot Applications. In IEEE (Eds.), Proc. 6th International Conference on Control, Automation and Robotics (ICCAR) (pp. 161-169). Singapore, SG.

MLA:

Muradi, Murad, and Rolf Wanka. "Processing Time Optimization for Robot Applications." Proceedings of the 6th International Conference on Control, Automation and Robotics (ICCAR), Singapore Ed. IEEE, 2020. 161-169.

BibTeX: Download