@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{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}, abstract = {The Robot Operating System (ROS) is the current de-facto standard in robot middlewares. The steadily increasing size of the user base results in a greater demand for training as well. User groups range from students in academia to industry professionals with a broad spectrum of developers in between. To deliver high quality training and education to any of these audiences, educators need to tailor individual curricula for any such training. In this paper, we present an approach to ease compiling curricula for ROS trainings based on a taxonomy of the teaching contents. The instructor can select a set of dedicated learning units and the system will automatically compile the teaching material based on the dependencies of the units selected and a set of parameters for a particular training. We walk through an example training to illustrate our work.}, 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} } @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{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} } @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{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{HofmannLimpertMatareetal.2019, author = {Hofmann, Till and Limpert, Nicolas and Matar{\´e}, Victor 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{AlhwarinFerreinScholl2019, author = {Alhwarin, Faraj and Ferrein, Alexander and Scholl, Ingrid}, title = {An Efficient Hashing Algorithm for NN Problem in HD Spaces}, series = {Lecture Notes in Computer Science}, booktitle = {Lecture Notes in Computer Science}, isbn = {978-303005498-4}, doi = {10.1007/978-3-030-05499-1_6}, pages = {101 -- 115}, year = {2019}, 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{FerreinBharatheeshaSchifferetal.2019, author = {Ferrein, Alexander and Bharatheesha, Mukunda and Schiffer, Stefan and Corbato, Carlos Hernandez}, title = {TRROS 2018 : Teaching Robotics with ROS Workshop at ERF 2018; Proceedings of the Workshop on Teaching Robotics with ROS (held at ERF 2018), co-located with European Robotics Forum 2018 (ERF 2018), Tampere, Finland, March 15th, 2018}, series = {CEUR Workshop Proceedings}, booktitle = {CEUR Workshop Proceedings}, number = {Vol-2329}, issn = {1613-0073}, pages = {68 Seiten}, year = {2019}, language = {en} } @inproceedings{FerreinSchollNeumannetal.2019, author = {Ferrein, Alexander and Scholl, Ingrid and Neumann, Tobias and Kr{\"u}ckel, Kai and Schiffer, Stefan}, title = {A system for continuous underground site mapping and exploration}, doi = {10.5772/intechopen.85859}, pages = {16 Seiten}, year = {2019}, language = {en} } @inproceedings{WiesenEngemannLimpertetal.2018, author = {Wiesen, Patrick and Engemann, Heiko and Limpert, Nicolas and Kallweit, Stephan}, title = {Learning by Doing - Mobile Robotics in the FH Aachen ROS Summer School}, series = {European Robotics Forum 2018, TRROS18 Workshop}, booktitle = {European Robotics Forum 2018, TRROS18 Workshop}, pages = {47 -- 58}, year = {2018}, language = {en} } @inproceedings{EngemannWiesenKallweitetal.2018, author = {Engemann, Heiko and Wiesen, Patrick and Kallweit, Stephan and Deshpande, Harshavardhan and Schleupen, Josef}, title = {Autonomous mobile manipulation using ROS}, series = {Advances in Service and Industrial Robotics}, booktitle = {Advances in Service and Industrial Robotics}, publisher = {Springer}, address = {Cham}, isbn = {978-3-319-61276-8}, doi = {10.1007/978-3-319-61276-8_43}, pages = {389 -- 401}, year = {2018}, 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{ZugNiemuellerHochgeschwenderetal.2017, author = {Zug, Sebastian and Niemueller, Tim and Hochgeschwender, Nico and Seidensticker, Kai and Seidel, Martin and Friedrich, Tim and Neumann, Tobias and Karras, Ulrich and Kraetzschmar, Gerhard K. and Ferrein, Alexander}, title = {An Integration Challenge to Bridge the Gap Among Industry-Inspired RoboCup Leagues}, 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_13}, pages = {157 -- 168}, year = {2017}, language = {en} } @inproceedings{StopforthDavrajhFerrein2017, author = {Stopforth, Riaan and Davrajh, Shaniel and Ferrein, Alexander}, title = {South African robotics entity for a collaboration initiative}, series = {Pattern Recognition Association of South Africa and Robotics and Mechatronics International Conference (PRASA-RobMech), 2016}, booktitle = {Pattern Recognition Association of South Africa and Robotics and Mechatronics International Conference (PRASA-RobMech), 2016}, publisher = {IEEE}, isbn = {978-1-5090-3335-5}, doi = {10.1109/RoboMech.2016.7813144}, pages = {1 -- 6}, year = {2017}, language = {en} } @inproceedings{WalentaSchellekensFerreinetal.2017, author = {Walenta, Robert and Schellekens, Twan and Ferrein, Alexander and Schiffer, Stefan}, title = {A decentralised system approach for controlling AGVs with ROS}, series = {AFRICON, Proceedings}, booktitle = {AFRICON, Proceedings}, publisher = {IEEE}, isbn = {978-1-5386-2775-4}, issn = {2153-0033}, doi = {10.1109/AFRCON.2017.8095693}, pages = {1436 -- 1441}, year = {2017}, language = {en} } @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} } @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} }