@inproceedings{StopforthDavrajhFerrein2017,
  author    = {Stopforth, Riaan and Davrajh, Shaniel and Ferrein, Alexander},
  title     = {Design considerations of the duo fugam dual rotor UAV},
  series = {2017 Pattern Recognition Association of South Africa and Robotics and Mechatronics (PRASA-RobMech)},
  booktitle = {2017 Pattern Recognition Association of South Africa and Robotics and Mechatronics (PRASA-RobMech)},
  isbn      = {978-1-5386-2314-5},
  doi       = {10.1109/RoboMech.2017.8261115},
  pages     = {7 -- 13},
  year      = {2017},
  language  = {en}
}
@article{SteinbauerFerrein2016,
  author    = {Steinbauer, Gerald and Ferrein, Alexander},
  title     = {20 Years of RoboCup},
  series = {KI - K{\"u}nstliche Intelligenz},
  volume    = {30},
  journal   = {KI - K{\"u}nstliche Intelligenz},
  number    = {3-4},
  publisher = {Springer},
  address   = {Berlin},
  issn      = {1610-1987},
  doi       = {10.1007/s13218-016-0442-z},
  pages     = {221 -- 224},
  year      = {2016},
  language  = {en}
}
@inproceedings{SteinbauerFerrein2019,
  author    = {Steinbauer, Gerald and Ferrein, Alexander},
  title     = {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.},
  series = {CEUR workshop proceedings},
  booktitle = {CEUR workshop proceedings},
  number    = {Vol-2325},
  issn      = {1613-0073},
  pages     = {46 Seiten},
  year      = {2019},
  language  = {en}
}
@inproceedings{SchulteTiggesMatheisRekeetal.2023,
  author    = {Schulte-Tigges, Joschua and Matheis, Dominik and Reke, Michael and Walter, Thomas and Kaszner, Daniel},
  title     = {Demonstrating a V2X enabled system for transition of control and minimum risk manoeuvre when leaving the operational design domain},
  series = {HCII 2023: HCI in Mobility, Transport, and Automotive Systems},
  booktitle = {HCII 2023: HCI in Mobility, Transport, and Automotive Systems},
  editor    = {Kr{\"o}mker, Heidi},
  publisher = {Springer},
  address   = {Cham},
  isbn      = {978-3-031-35677-3 (Print)},
  doi       = {10.1007/978-3-031-35678-0_12},
  pages     = {200 -- 210},
  year      = {2023},
  abstract  = {Modern implementations of driver assistance systems are evolving from a pure driver assistance to a independently acting automation system. Still these systems are not covering the full vehicle usage range, also called operational design domain, which require the human driver as fall-back mechanism. Transition of control and potential minimum risk manoeuvres are currently research topics and will bridge the gap until full autonomous vehicles are available. The authors showed in a demonstration that the transition of control mechanisms can be further improved by usage of communication technology. Receiving the incident type and position information by usage of standardised vehicle to everything (V2X) messages can improve the driver safety and comfort level. The connected and automated vehicle's software framework can take this information to plan areas where the driver should take back control by initiating a transition of control which can be followed by a minimum risk manoeuvre in case of an unresponsive driver. This transition of control has been implemented in a test vehicle and was presented to the public during the IEEE IV2022 (IEEE Intelligent Vehicle Symposium) in Aachen, Germany.},
  language  = {en}
}
@article{SchulteTiggesFoersterNikolovskietal.2022,
  author    = {Schulte-Tigges, Joschua and F{\"o}rster, Marco and Nikolovski, Gjorgji and Reke, Michael and Ferrein, Alexander and Kaszner, Daniel and Matheis, Dominik and Walter, Thomas},
  title     = {Benchmarking of various LiDAR sensors for use in self-driving vehicles in real-world environments},
  series = {Sensors},
  volume    = {22},
  journal   = {Sensors},
  number    = {19},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {1424-8220},
  doi       = {10.3390/s22197146},
  pages     = {20 Seiten},
  year      = {2022},
  abstract  = {Abstract In this paper, we report on our benchmark results of the LiDAR sensors Livox Horizon, Robosense M1, Blickfeld Cube, Blickfeld Cube Range, Velodyne Velarray H800, and Innoviz Pro. The idea was to test the sensors in different typical scenarios that were defined with real-world use cases in mind, in order to find a sensor that meet the requirements of self-driving vehicles. For this, we defined static and dynamic benchmark scenarios. In the static scenarios, both LiDAR and the detection target do not move during the measurement. In dynamic scenarios, the LiDAR sensor was mounted on the vehicle which was driving toward the detection target. We tested all mentioned LiDAR sensors in both scenarios, show the results regarding the detection accuracy of the targets, and discuss their usefulness for deployment in self-driving cars.},
  language  = {en}
}
@inproceedings{SchollBartellaMoluluoetal.2019,
  author    = {Scholl, Ingrid and Bartella, Alex and Moluluo, Cem and Ertural, Berat and Laing, Frederic and Suder, Sebastian},
  title     = {MedicVR : Acceleration and Enhancement Techniques for Direct Volume Rendering in Virtual Reality},
  series = {Bildverarbeitung f{\"u}r die Medizin 2019 : Algorithmen - Systeme - Anwendungen},
  booktitle = {Bildverarbeitung f{\"u}r die Medizin 2019 : Algorithmen - Systeme - Anwendungen},
  publisher = {Springer Vieweg},
  address   = {Wiesbaden},
  isbn      = {978-3-658-25326-4},
  doi       = {10.1007/978-3-658-25326-4_32},
  pages     = {152 -- 157},
  year      = {2019},
  language  = {en}
}
@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}
}
@article{SchifferFerrein2016,
  author    = {Schiffer, Stefan and Ferrein, Alexander},
  title     = {Decision-Theoretic Planning with Fuzzy Notions in GOLOG},
  series = {International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems},
  volume    = {24},
  journal   = {International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems},
  number    = {Issue Suppl. 2},
  publisher = {World Scientific},
  address   = {Singapur},
  issn      = {1793-6411},
  doi       = {10.1142/S0218488516400134},
  pages     = {123 -- 143},
  year      = {2016},
  abstract  = {In this paper we present an extension of the action language Golog that allows for using fuzzy notions in non-deterministic argument choices and the reward function in decision-theoretic planning. Often, in decision-theoretic planning, it is cumbersome to specify the set of values to pick from in the non-deterministic-choice-of-argument statement. Also, even for domain experts, it is not always easy to specify a reward function. Instead of providing a finite domain for values in the non-deterministic-choice-of-argument statement in Golog, we now allow for stating the argument domain by simply providing a formula over linguistic terms and fuzzy uents. In Golog's forward-search DT planning algorithm, these formulas are evaluated in order to find the agent's optimal policy. We illustrate this in the Diner Domain where the agent needs to calculate the optimal serving order.},
  language  = {en}
}
@inproceedings{SchifferFerrein2017,
  author    = {Schiffer, Stefan and Ferrein, Alexander},
  title     = {A System Layout for Cognitive Service Robots},
  series = {Cognitive Robot Architectures. Proceedings of EUCognition 2016},
  booktitle = {Cognitive Robot Architectures. Proceedings of EUCognition 2016},
  issn      = {1613-0073},
  pages     = {44 -- 45},
  year      = {2017},
  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},
  publisher = {IEEE},
  address   = {New York, NY},
  isbn      = {978-1-7281-4162-6},
  doi       = {10.1109/SAUPEC/RobMech/PRASA48453.2020.9041020},
  pages     = {1 -- 6},
  year      = {2020},
  abstract  = {In this paper we report on an architecture for a self-driving car that is based on ROS2. Self-driving cars have to take decisions based on their sensory input in real-time, providing high reliability with a strong demand in functional safety. In principle, self-driving cars are robots. However, typical robot software, in general, and the previous version of the Robot Operating System (ROS), in particular, does not always meet these requirements. With the successor ROS2 the situation has changed and it might be considered as a solution for automated and autonomous driving. Existing robotic software based on ROS was not ready for safety critical applications like self-driving cars. We propose an architecture for using ROS2 for a self-driving car that enables safe and reliable real-time behaviour, but keeping the advantages of ROS such as a distributed architecture and standardised message types. First experiments with an automated real passenger car at lower and higher speed-levels show that our approach seems feasible for autonomous driving under the necessary real-time conditions.},
  language  = {en}
}