@inproceedings{ChavezBermudezCruzCastanonRuchayetal.2022, author = {Chavez Bermudez, Victor Francisco and Cruz Castanon, Victor Fernando and Ruchay, Marco and Wollert, J{\"o}rg}, title = {Rapid prototyping framework for automation applications based on IO-Link}, series = {Tagungsband AALE 2022}, booktitle = {Tagungsband AALE 2022}, editor = {Leipzig, Hochschule f{\"u}r Technik, Wirtschaft und Kultur}, address = {Leipzig}, isbn = {978-3-910103-00-9}, doi = {10.33968/2022.28}, pages = {8 Seiten}, year = {2022}, abstract = {The development of protype applications with sensors and actuators in the automation industry requires tools that are independent of manufacturer, and are flexible enough to be modified or extended for any specific requirements. Currently, developing prototypes with industrial sensors and actuators is not straightforward. First of all, the exchange of information depends on the industrial protocol that these devices have. Second, a specific configuration and installation is done based on the hardware that is used, such as automation controllers or industrial gateways. This means that the development for a specific industrial protocol, highly depends on the hardware and the software that vendors provide. In this work we propose a rapid-prototyping framework based on Arduino to solve this problem. For this project we have focused to work with the IO-Link protocol. The framework consists of an Arduino shield that acts as the physical layer, and a software that implements the IO-Link Master protocol. The main advantage of such framework is that an application with industrial devices can be rapid-prototyped with ease as its vendor independent, open-source and can be ported easily to other Arduino compatible boards. In comparison, a typical approach requires proprietary hardware, is not easy to port to another system and is closed-source.}, language = {en} } @inproceedings{ChajanSchulteTiggesRekeetal.2021, author = {Chajan, Eduard and Schulte-Tigges, Joschua and Reke, Michael and Ferrein, Alexander and Matheis, Dominik and Walter, Thomas}, title = {GPU based model-predictive path control for self-driving vehicles}, series = {IEEE Intelligent Vehicles Symposium (IV)}, booktitle = {IEEE Intelligent Vehicles Symposium (IV)}, publisher = {IEEE}, isbn = {978-1-7281-5394-0}, doi = {10.1109/IV48863.2021.9575619}, pages = {1243 -- 1248}, year = {2021}, abstract = {One central challenge for self-driving cars is a proper path-planning. Once a trajectory has been found, the next challenge is to accurately and safely follow the precalculated path. The model-predictive controller (MPC) is a common approach for the lateral control of autonomous vehicles. The MPC uses a vehicle dynamics model to predict the future states of the vehicle for a given prediction horizon. However, in order to achieve real-time path control, the computational load is usually large, which leads to short prediction horizons. To deal with the computational load, the control algorithm can be parallelized on the graphics processing unit (GPU). In contrast to the widely used stochastic methods, in this paper we propose a deterministic approach based on grid search. Our approach focuses on systematically discovering the search area with different levels of granularity. To achieve this, we split the optimization algorithm into multiple iterations. The best sequence of each iteration is then used as an initial solution to the next iteration. The granularity increases, resulting in smooth and predictable steering angle sequences. We present a novel GPU-based algorithm and show its accuracy and realtime abilities with a number of real-world experiments.}, language = {en} } @inproceedings{UlmerBraunChengetal.2021, author = {Ulmer, Jessica and Braun, Sebastian and Cheng, Chi-Tsun and Dowey, Steve and Wollert, J{\"o}rg}, title = {Adapting Augmented Reality Systems to the users' needs using Gamification and error solving methods}, series = {Procedia CIRP}, volume = {104}, booktitle = {Procedia CIRP}, publisher = {Elsevier}, address = {Amsterdam}, issn = {2212-8271}, doi = {10.1016/j.procir.2021.11.024}, pages = {140 -- 145}, year = {2021}, abstract = {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.}, language = {en} } @inproceedings{HueningStuettgen2021, author = {H{\"u}ning, Felix and St{\"u}ttgen, Marcel}, title = {Work in Progress: Interdisciplinary projects in times of COVID-19 crisis - challenges, risks and chances}, series = {2021 IEEE Global Engineering Education Conference (EDUCON)}, booktitle = {2021 IEEE Global Engineering Education Conference (EDUCON)}, doi = {10.1109/EDUCON46332.2021.9454006}, pages = {1175 -- 1179}, year = {2021}, language = {en} } @inproceedings{FerreinMeessenLimpertetal.2021, author = {Ferrein, Alexander and Meeßen, Marcus and Limpert, Nicolas and Schiffer, Stefan}, title = {Compiling ROS Schooling Curricula via Contentual Taxonomies}, series = {Robotics in Education}, booktitle = {Robotics in Education}, editor = {Lepuschitz, Wilfried}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-67411-3}, doi = {10.1007/978-3-030-67411-3_5}, pages = {49 -- 60}, year = {2021}, language = {en} } @inproceedings{DeyElsenFerreinetal.2021, author = {Dey, Thomas and Elsen, Ingo and Ferrein, Alexander and Frauenrath, Tobias and Reke, Michael and Schiffer, Stefan}, title = {CO2 Meter: a do-it-yourself carbon dioxide measuring device for the classroom}, series = {PETRA 2021: The 14th PErvasive Technologies Related to Assistive Environments Conference}, booktitle = {PETRA 2021: The 14th PErvasive Technologies Related to Assistive Environments Conference}, editor = {Makedon, Fillia}, publisher = {Association for Computing Machinery}, address = {New York}, isbn = {9781450387927}, doi = {10.1145/3453892.3462697}, pages = {292 -- 299}, year = {2021}, abstract = {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.}, language = {en} } @inproceedings{KirschMatareFerreinetal.2020, author = {Kirsch, Maximilian and Matar{\´e}, Victor and Ferrein, Alexander and Schiffer, Stefan}, title = {Integrating golog++ and ROS for Practical and Portable High-level Control}, series = {12th International Conference on Agents and Artificial Intelligence}, booktitle = {12th International Conference on Agents and Artificial Intelligence}, doi = {10.5220/0008984406920699}, year = {2020}, language = {en} } @inproceedings{RekePeterSchulteTiggesetal.2020, author = {Reke, Michael and Peter, Daniel and Schulte-Tigges, Joschua and Schiffer, Stefan and Ferrein, Alexander and Walter, Thomas and Matheis, Dominik}, title = {A Self-Driving Car Architecture in ROS2}, series = {2020 International SAUPEC/RobMech/PRASA Conference, Cape Town, South Africa}, booktitle = {2020 International SAUPEC/RobMech/PRASA Conference, Cape Town, South Africa}, isbn = {978-1-7281-4162-6}, doi = {10.1109/SAUPEC/RobMech/PRASA48453.2020.9041020}, pages = {1 -- 6}, year = {2020}, language = {en} } @inproceedings{UlmerBraunChengetal.2020, author = {Ulmer, Jessica and Braun, Sebastian and Cheng, Chi-Tsun and Dowey, Steve and Wollert, J{\"o}rg}, title = {Gamified Virtual Reality Training Environment for the Manufacturing Industry}, doi = {10.1109/ME49197.2020.9286661}, pages = {1 -- 6}, year = {2020}, language = {de} } @inproceedings{MatareSchifferFerrein2019, author = {Matar{\´e}, Victor and Schiffer, Stefan and Ferrein, Alexander}, title = {golog++ : An integrative system design}, series = {CogRob 2018. Cognitive Robotics Workshop : Proceedings of the 11th Cognitive Robotics Workshop 2018 co-located with 16th International Conference on Principles of Knowledge Representation and Reasoning (KR 2018) Tempe, AZ, USA, October 27th, 2018}, booktitle = {CogRob 2018. Cognitive Robotics Workshop : Proceedings of the 11th Cognitive Robotics Workshop 2018 co-located with 16th International Conference on Principles of Knowledge Representation and Reasoning (KR 2018) Tempe, AZ, USA, October 27th, 2018}, editor = {Steinbauer, Gerald and Ferrein, Alexander}, issn = {1613-0073}, pages = {29 -- 35}, year = {2019}, language = {en} }