@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}
}
@article{BraunChengDoweyetal.2021,
  author    = {Braun, Sebastian and Cheng, Chi-Tsun and Dowey, Steve and Wollert, J{\"o}rg},
  title     = {Performance evaluation of skill-based order-assignment in production environments with multi-agent systems},
  series = {IEEE Journal of Emerging and Selected Topics in Industrial Electronics},
  journal   = {IEEE Journal of Emerging and Selected Topics in Industrial Electronics},
  number    = {Early Access},
  publisher = {IEEE},
  address   = {New York},
  issn      = {2687-9735},
  doi       = {10.1109/JESTIE.2021.3108524},
  year      = {2021},
  abstract  = {The fourth industrial revolution introduces disruptive technologies to production environments. One of these technologies are multi-agent systems (MASs), where agents virtualize machines. However, the agent's actual performances in production environments can hardly be estimated as most research has been focusing on isolated projects and specific scenarios. We address this gap by implementing a highly connected and configurable reference model with quantifiable key performance indicators (KPIs) for production scheduling and routing in single-piece workflows. Furthermore, we propose an algorithm to optimize the search of extrema in highly connected distributed systems. The benefits, limits, and drawbacks of MASs and their performances are evaluated extensively by event-based simulations against the introduced model, which acts as a benchmark. Even though the performance of the proposed MAS is, on average, slightly lower than the reference system, the increased flexibility allows it to find new solutions and deliver improved factory-planning outcomes. Our MAS shows an emerging behavior by using flexible production techniques to correct errors and compensate for bottlenecks. This increased flexibility offers substantial improvement potential. The general model in this paper allows the transfer of the results to estimate real systems or other models.},
  language  = {en}
}
@inproceedings{ChavezBermudezWollert2022,
  author    = {Chavez Bermudez, Victor Francisco and Wollert, J{\"o}rg},
  title     = {10BASE-T1L industry 4.0 smart switch for field devices based on IO-Link},
  series = {2022 IEEE 18th International Conference on Factory Communication Systems (WFCS)},
  booktitle = {2022 IEEE 18th International Conference on Factory Communication Systems (WFCS)},
  publisher = {IEEE},
  isbn      = {978-1-6654-1086-1},
  doi       = {10.1109/WFCS53837.2022.9779176},
  pages     = {4 Seiten},
  year      = {2022},
  abstract  = {The recent amendment to the Ethernet physical layer known as the IEEE 802.3cg specification, allows to connect devices up to a distance of one kilometer and delivers a maximum of 60 watts of power over a twisted pair of wires. This new standard, also known as 10BASE-TIL, promises to overcome the limits of current physical layers used for field devices and bring them a step closer to Ethernet-based applications. The main advantage of 10BASE- TIL is that it can deliver power and data over the same line over a long distance, where traditional solutions (e.g., CAN, IO-Link, HART) fall short and cannot match its 10 Mbps bandwidth. Due to its recentness, IOBASE- TIL is still not integrated into field devices and it has been less than two years since silicon manufacturers released the first Ethernet-PHY chips. In this paper, we present a design proposal on how field devices could be integrated into a IOBASE-TIL smart switch that allows plug-and-play connectivity for sensors and actuators and is compliant with the Industry 4.0 vision. Instead of presenting a new field-level protocol for this work, we have decided to adopt the IO-Link specification which already includes a plug-and-play approach with features such as diagnosis and device configuration. The main objective of this work is to explore how field devices could be integrated into 10BASE-TIL Ethernet, its adaption with a well-known protocol, and its integration with Industry 4.0 technologies.},
  language  = {en}
}
@inproceedings{UlmerBraunChengetal.2022,
  author    = {Ulmer, Jessica and Braun, Sebastian and Cheng, Chi-Tsun and Dowey, Steve and Wollert, J{\"o}rg},
  title     = {Usage of digital twins for gamification applications in manufacturing},
  series = {Procedia CIRP},
  volume    = {107},
  booktitle = {Procedia CIRP},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {2212-8271},
  doi       = {10.1016/j.procir.2022.05.044},
  pages     = {675 -- 680},
  year      = {2022},
  abstract  = {Gamification applications are on the rise in the manufacturing sector to customize working scenarios, offer user-specific feedback, and provide personalized learning offerings. Commonly, different sensors are integrated into work environments to track workers' actions. Game elements are selected according to the work task and users' preferences. However, implementing gamified workplaces remains challenging as different data sources must be established, evaluated, and connected. Developers often require information from several areas of the companies to offer meaningful gamification strategies for their employees. Moreover, work environments and the associated support systems are usually not flexible enough to adapt to personal needs. Digital twins are one primary possibility to create a uniform data approach that can provide semantic information to gamification applications. Frequently, several digital twins have to interact with each other to provide information about the workplace, the manufacturing process, and the knowledge of the employees. This research aims to create an overview of existing digital twin approaches for digital support systems and presents a concept to use digital twins for gamified support and training systems. The concept is based upon the Reference Architecture Industry 4.0 (RAMI 4.0) and includes information about the whole life cycle of the assets. It is applied to an existing gamified training system and evaluated in the Industry 4.0 model factory by an example of a handle mounting.},
  language  = {en}
}
@inproceedings{HofmannLimpertMatareetal.2019,
  author    = {Hofmann, Till and Limpert, Nicolas and Matar{\´e}, Viktor and Ferrein, Alexander and Lakemeyer, Gerhard},
  title     = {Winning the RoboCup Logistics League with Fast Navigation, Precise Manipulation, and Robust Goal Reasoning},
  series = {RoboCup 2019: Robot World Cup XXIII. RoboCup},
  booktitle = {RoboCup 2019: Robot World Cup XXIII. RoboCup},
  publisher = {Springer},
  address   = {Cham},
  isbn      = {978-3-030-35699-6},
  doi       = {10.1007/978-3-030-35699-6_41},
  pages     = {504 -- 516},
  year      = {2019},
  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{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{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}
}