TY  - CHAP
A1  - Ferrein, Alexander
A1  - Meeßen, Marcus
A1  - Limpert, Nicolas
A1  - Schiffer, Stefan
ED  - Lepuschitz, Wilfried
T1  - Compiling ROS Schooling Curricula via Contentual Taxonomies
T2  - Robotics in Education
Y1  - 2021
SN  - 978-3-030-67411-3
U6  - http://dx.doi.org/10.1007/978-3-030-67411-3_5
N1  - RiE: International Conference on Robotics in Education (RiE);
Advances in Intelligent Systems and Computing book series (AISC, volume 1316)
SP  - 49
EP  - 60
PB  - Springer
CY  - Cham
ER  - 
TY  - CHAP
A1  - Dey, Thomas
A1  - Elsen, Ingo
A1  - Ferrein, Alexander
A1  - Frauenrath, Tobias
A1  - Reke, Michael
A1  - Schiffer, Stefan
ED  - Makedon, Fillia
T1  - CO2 Meter: a do-it-yourself carbon dioxide measuring device for the classroom
T2  - PETRA 2021: The 14th PErvasive Technologies Related to Assistive Environments Conference
N2  - In this paper we report on CO2 Meter, a do-it-yourself carbon dioxide measuring device for the classroom. Part of the current measures for dealing with the SARS-CoV-2 pandemic is proper ventilation in indoor settings. This is especially important in schools with students coming back to the classroom even with high incidents rates. Static ventilation patterns do not consider the individual situation for a particular class. Influencing factors like the type of activity, the physical structure or the room occupancy are not incorporated. Also, existing devices are rather expensive and often provide only limited information and only locally without any networking. This leaves the potential of analysing the situation across different settings untapped. Carbon dioxide level can be used as an indicator of air quality, in general, and of aerosol load in particular. Since, according to the latest findings, SARS-CoV-2 can be transmitted primarily in the form of aerosols, carbon dioxide may be used as a proxy for the risk of a virus infection. Hence, schools could improve the indoor air quality and potentially reduce the infection risk if they actually had measuring devices available in the classroom. Our device supports schools in ventilation and it allows for collecting data over the Internet to enable a detailed data analysis and model generation. First deployments in schools at different levels were received very positively. A pilot installation with a larger data collection and analysis is underway.
KW  - embedded hardware
KW  - sensor networks
KW  - information systems
KW  - education
KW  - do-it-yourself
Y1  - 2021
SN  - 9781450387927
U6  - http://dx.doi.org/10.1145/3453892.3462697
N1  - PETRA '21: The 14th PErvasive Technologies Related to Assistive Environments Conference Corfu Greece 29 June 2021- 2 July 2021
SP  - 292
EP  - 299
PB  - Association for Computing Machinery
CY  - New York
ER  - 
TY  - CHAP
A1  - Ulmer, Jessica
A1  - Braun, Sebastian
A1  - Cheng, Chi-Tsun
A1  - Dowey, Steve
A1  - Wollert, Jörg
T1  - Adapting Augmented Reality Systems to the users’ needs using Gamification and error solving methods
T2  - Procedia CIRP
N2  - Animations of virtual items in AR support systems are typically predefined and lack interactions with dynamic physical environments. AR applications rarely consider users’ preferences and do not provide customized spontaneous support under unknown situations. This research focuses on developing adaptive, error-tolerant AR systems based on directed acyclic graphs and error resolving strategies. Using this approach, users will have more freedom of choice during AR supported work, which leads to more efficient workflows. Error correction methods based on CAD models and predefined process data create individual support possibilities. The framework is implemented in the Industry 4.0 model factory at FH Aachen.
KW  - Augmented Reality
KW  - Adaptive Systems
KW  - Gamification
KW  - Error Recovery
Y1  - 2021
U6  - http://dx.doi.org/10.1016/j.procir.2021.11.024
SN  - 2212-8271
N1  - Part of special issue: 54th CIRP CMS 2021 - Towards Digitalized Manufacturing 4.0
VL  - 104
SP  - 140
EP  - 145
PB  - Elsevier
CY  - Amsterdam
ER  - 
TY  - JOUR
A1  - Engemann, Heiko
A1  - Cönen, Patrick
A1  - Dawar, Harshal
A1  - Du, Shengzhi
A1  - Kallweit, Stephan
T1  - A robot-assisted large-scale inspection of wind turbine blades in manufacturing using an autonomous mobile manipulator
JF  - Applied Sciences
N2  - Wind energy represents the dominant share of renewable energies. The rotor blades of a wind turbine are typically made from composite material, which withstands high forces during rotation. The huge dimensions of the rotor blades complicate the inspection processes in manufacturing. The automation of inspection processes has a great potential to increase the overall productivity and to create a consistent reliable database for each individual rotor blade. The focus of this paper is set on the process of rotor blade inspection automation by utilizing an autonomous mobile manipulator. The main innovations include a novel path planning strategy for zone-based navigation, which enables an intuitive right-hand or left-hand driving behavior in a shared human–robot workspace. In addition, we introduce a new method for surface orthogonal motion planning in connection with large-scale structures. An overall execution strategy controls the navigation and manipulation processes of the long-running inspection task. The implemented concepts are evaluated in simulation and applied in a real-use case including the tip of a rotor blade form.
KW  - mobile manipulation
KW  - large-scale inspection
KW  - wind turbine production
KW  - autonomous navigation
KW  - surface-orthogonal path planning
Y1  - 2021
U6  - http://dx.doi.org/10.3390/app11199271
SN  - 2076-3417
N1  - Belongs to the Special Issue "Advances in Industrial Robotics and Intelligent Systems"
VL  - 11
IS  - 19
SP  - 1
EP  - 22
PB  - MDPI
CY  - Basel
ER  -