TY - CHAP A1 - Viehmann, Tarik A1 - Limpert, Nicolas A1 - Hofmann, Till A1 - Henning, Mike A1 - Ferrein, Alexander A1 - Lakemeyer, Gerhard ED - Eguchi, Amy ED - Lau, Nuno ED - Paetzel-Prüsmann, Maike ED - Wanichanon, Thanapat T1 - Winning the RoboCup logistics league with visual servoing and centralized goal reasoning T2 - RoboCup 2022 N2 - The RoboCup Logistics League (RCLL) is a robotics competition in a production logistics scenario in the context of a Smart Factory. In the competition, a team of three robots needs to assemble products to fulfill various orders that are requested online during the game. This year, the Carologistics team was able to win the competition with a new approach to multi-agent coordination as well as significant changes to the robot’s perception unit and a pragmatic network setup using the cellular network instead of WiFi. In this paper, we describe the major components of our approach with a focus on the changes compared to the last physical competition in 2019. Y1 - 2023 SN - 978-3-031-28468-7 (Print) SN - 978-3-031-28469-4 (Online) U6 - http://dx.doi.org/https://doi.org/10.1007/978-3-031-28469-4_25 N1 - Robot World Cup, RoboCup 2022. 17. July 2023. Bangkok, Thailand. Part of the Lecture Notes in Computer Science book series (LNAI,volume 13561) SP - 300 EP - 312 PB - Springer CY - Cham ER - TY - CHAP A1 - Arndt, Tobias A1 - Conzen, Max A1 - Elsen, Ingo A1 - Ferrein, Alexander A1 - Galla, Oskar A1 - Köse, Hakan A1 - Schiffer, Stefan A1 - Tschesche, Matteo T1 - Anomaly detection in the metal-textile industry for the reduction of the cognitive load of quality control workers T2 - PETRA '23: Proceedings of the 16th International Conference on PErvasive Technologies Related to Assistive Environments N2 - This paper presents an approach for reducing the cognitive load for humans working in quality control (QC) for production processes that adhere to the 6σ -methodology. While 100% QC requires every part to be inspected, this task can be reduced when a human-in-the-loop QC process gets supported by an anomaly detection system that only presents those parts for manual inspection that have a significant likelihood of being defective. This approach shows good results when applied to image-based QC for metal textile products. KW - Datasets KW - Neural networks KW - Anomaly detection KW - Quality control KW - Process optimization Y1 - 2023 SN - 9798400700699 U6 - http://dx.doi.org/10.1145/3594806.3596558 N1 - PETRA '23: Proceedings of the 16th International Conference on Pervasive Technologies Related to Assistive Environments, Corfu Greece, July 5 - 7, 2023. SP - 535 EP - 542 PB - ACM ER -