@inproceedings{SchleupenEngemannBagherietal.2017,
  author    = {Schleupen, Josef and Engemann, Heiko and Bagheri, Mohsen and Kallweit, Stephan and Dahmann, Peter},
  title     = {Developing a climbing maintenance robot for tower and rotor blade service of wind turbines},
  series = {Advances in Robot Design and Intelligent Control : Proceedings of the 25th Conference on Robotics in Alpe-Adria-Danube Region (RAAD16)},
  booktitle = {Advances in Robot Design and Intelligent Control : Proceedings of the 25th Conference on Robotics in Alpe-Adria-Danube Region (RAAD16)},
  publisher = {Springer},
  address   = {Cham},
  isbn      = {978-3-319-49058-8},
  doi       = {10.1007/978-3-319-49058-8_34},
  pages     = {310 -- 319},
  year      = {2017},
  language  = {en}
}
@inproceedings{LeingartnerMaurerSteinbaueretal.2013,
  author    = {Leingartner, Max and Maurer, Johannes and Steinbauer, Gerald and Ferrein, Alexander},
  title     = {Evaluation of sensors and mapping approaches for disasters in tunnels},
  series = {IEEE International Symposium on Safety, Security, and Rescue Robotics : SSRR : 21-26 Oct. 2013, Linkoping, Sweden},
  booktitle = {IEEE International Symposium on Safety, Security, and Rescue Robotics : SSRR : 21-26 Oct. 2013, Linkoping, Sweden},
  organization    = {Institute of Electrical and Electronics Engineers},
  isbn      = {978-1-4799-0879-0},
  pages     = {1 -- 7},
  year      = {2013},
  language  = {en}
}
@inproceedings{NiemuellerReuterFerreinetal.2016,
  author    = {Niemueller, Tim and Reuter, Sebastian and Ferrein, Alexander and Jeschke, Sabina and Lakemeyer, Gerhard},
  title     = {Evaluation of the RoboCup Logistics League and Derived Criteria for Future Competitions},
  series = {RoboCup 2015: Robot World Cup XIX},
  booktitle = {RoboCup 2015: Robot World Cup XIX},
  editor    = {Almeida, Luis},
  publisher = {Springer International Publishing},
  address   = {Cham},
  isbn      = {978-3-319-29339-4},
  doi       = {10.1007/978-3-319-29339-4_3},
  pages     = {31 -- 43},
  year      = {2016},
  language  = {en}
}
@inproceedings{NiemuellerReuterFerrein2016,
  author    = {Niemueller, Tim and Reuter, Sebastian and Ferrein, Alexander},
  title     = {Fawkes for the RoboCup Logistics League},
  series = {RoboCup 2015: Robot World Cup XIX},
  booktitle = {RoboCup 2015: Robot World Cup XIX},
  editor    = {Almeida, Luis},
  publisher = {Springer International Publishing},
  address   = {Cham},
  isbn      = {978-3-319-29339-4},
  doi       = {10.1007/978-3-319-29339-4_31},
  pages     = {365 -- 373},
  year      = {2016},
  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},
  series = {Proceedings of the 2020 19th International Conference on Mechatronics - Mechatronika (ME)},
  booktitle = {Proceedings of the 2020 19th International Conference on Mechatronics - Mechatronika (ME)},
  publisher = {IEEE},
  address   = {New York, NY},
  doi       = {10.1109/ME49197.2020.9286661},
  pages     = {1 -- 6},
  year      = {2020},
  abstract  = {Industry 4.0 imposes many challenges for manufacturing companies and their employees. Innovative and effective training strategies are required to cope with fast-changing production environments and new manufacturing technologies. Virtual Reality (VR) offers new ways of on-the-job, on-demand, and off-premise training. A novel concept and evaluation system combining Gamification and VR practice for flexible assembly tasks is proposed in this paper and compared to existing works. It is based on directed acyclic graphs and a leveling system. The concept enables a learning speed which is adjustable to the users' pace and dynamics, while the evaluation system facilitates adaptive work sequences and allows employee-specific task fulfillment. The concept was implemented and analyzed in the Industry 4.0 model factory at FH Aachen for mechanical assembly jobs.},
  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}
}
@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},
  address   = {New York, NY},
  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{NiemuellerNeumannHenkeetal.2017,
  author    = {Niemueller, Tim and Neumann, Tobias and Henke, Christoph and Sch{\"o}nitz, Sebastian and Reuter, Sebastian and Ferrein, Alexander and Jeschke, Sabina and Lakemeyer, Gerhard},
  title     = {Improvements for a robust production in the RoboCup logistics league 2016},
  series = {RoboCup 2016: Robot World Cup XX. RoboCup 2016.},
  booktitle = {RoboCup 2016: Robot World Cup XX. RoboCup 2016.},
  publisher = {Springer},
  address   = {Cham},
  isbn      = {978-3-319-68792-6},
  doi       = {10.1007/978-3-319-68792-6_49},
  pages     = {589 -- 600},
  year      = {2017},
  language  = {en}
}
@inproceedings{AlhwarinFerreinGebhardtetal.2015,
  author    = {Alhwarin, Faraj and Ferrein, Alexander and Gebhardt, Andreas and Kallweit, Stephan and Scholl, Ingrid and Tedjasukmana, Osmond Sanjaya},
  title     = {Improving additive manufacturing by image processing and robotic milling},
  series = {2015 IEEE International Conference on Automation Science and Engineering (CASE), Aug 24-28, 2015 Gothenburg, Sweden},
  booktitle = {2015 IEEE International Conference on Automation Science and Engineering (CASE), Aug 24-28, 2015 Gothenburg, Sweden},
  doi       = {10.1109/CoASE.2015.7294217},
  pages     = {924 -- 929},
  year      = {2015},
  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 = {Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 2},
  booktitle = {Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 2},
  publisher = {SciTePress},
  address   = {Set{\´u}bal, Portugal},
  doi       = {10.5220/0008984406920699},
  pages     = {692 -- 699},
  year      = {2020},
  abstract  = {The field of Cognitive Robotics aims at intelligent decision making of autonomous robots. It has matured over the last 25 or so years quite a bit. That is, a number of high-level control languages and architectures have emerged from the field. One concern in this regard is the action language GOLOG. GOLOG has been used in a rather large number of applications as a high-level control language ranging from intelligent service robots to soccer robots. For the lower level robot software, the Robot Operating System (ROS) has been around for more than a decade now and it has developed into the standard middleware for robot applications. ROS provides a large number of packages for standard tasks in robotics like localisation, navigation, and object recognition. Interestingly enough, only little work within ROS has gone into the high-level control of robots. In this paper, we describe our approach to marry the GOLOG action language with ROS. In particular, we present our architecture on inte grating golog++, which is based on the GOLOG dialect Readylog, with the Robot Operating System. With an example application on the Pepper service robot, we show how primitive actions can be easily mapped to the ROS ActionLib framework and present our control architecture in detail.},
  language  = {en}
}