@article{UlmerBraunChengetal.2023, author = {Ulmer, Jessica and Braun, Sebastian and Cheng, Chi-Tsun and Dowey, Steve and Wollert, J{\"o}rg}, title = {A human factors-aware assistance system in manufacturing based on gamification and hardware modularisation}, series = {International Journal of Production Research}, journal = {International Journal of Production Research}, publisher = {Taylor \& Francis}, issn = {0020-7543 (Print)}, doi = {10.1080/00207543.2023.2166140}, year = {2023}, abstract = {Assistance systems have been widely adopted in the manufacturing sector to facilitate various processes and tasks in production environments. However, existing systems are mostly equipped with rigid functional logic and do not provide individual user experiences or adapt to their capabilities. This work integrates human factors in assistance systems by adjusting the hardware and instruction presented to the workers' cognitive and physical demands. A modular system architecture is designed accordingly, which allows a flexible component exchange according to the user and the work task. Gamification, the use of game elements in non-gaming contexts, has been further adopted in this work to provide level-based instructions and personalised feedback. The developed framework is validated by applying it to a manual workstation for industrial assembly routines.}, language = {en} } @inproceedings{ViehmannLimpertHofmannetal.2023, author = {Viehmann, Tarik and Limpert, Nicolas and Hofmann, Till and Henning, Mike and Ferrein, Alexander and Lakemeyer, Gerhard}, title = {Winning the RoboCup logistics league with visual servoing and centralized goal reasoning}, series = {RoboCup 2022: Robot World Cup XXV}, booktitle = {RoboCup 2022: Robot World Cup XXV}, editor = {Eguchi, Amy and Lau, Nuno and Paetzel-Pr{\"u}smann, Maike and Wanichanon, Thanapat}, publisher = {Springer}, address = {Cham}, isbn = {978-3-031-28468-7 (Print)}, doi = {https://doi.org/10.1007/978-3-031-28469-4_25}, pages = {300 -- 312}, year = {2023}, abstract = {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.}, language = {en} }