@incollection{NiemuellerLakemeyerReuteretal.2017, author = {Niemueller, T. and Lakemeyer, G. and Reuter, S. and Jeschke, S. and Ferrein, Alexander}, title = {Benchmarking of Cyber-Physical Systems in Industrial Robotics: The RoboCup Logistics League as a CPS Benchmark Blueprint}, series = {Cyber-Physical Systems: Foundations, Principles and Applications}, booktitle = {Cyber-Physical Systems: Foundations, Principles and Applications}, publisher = {Academic Press}, address = {London}, doi = {10.1016/B978-0-12-803801-7.00013-4}, pages = {193 -- 207}, year = {2017}, abstract = {In the future, we expect manufacturing companies to follow a new paradigm that mandates more automation and autonomy in production processes. Such smart factories will offer a variety of production technologies as services that can be combined ad hoc to produce a large number of different product types and variants cost-effectively even in small lot sizes. This is enabled by cyber-physical systems that feature flexible automated planning methods for production scheduling, execution control, and in-factory logistics. During development, testbeds are required to determine the applicability of integrated systems in such scenarios. Furthermore, benchmarks are needed to quantify and compare system performance in these industry-inspired scenarios at a comprehensible and manageable size which is, at the same time, complex enough to yield meaningful results. In this chapter, based on our experience in the RoboCup Logistics League (RCLL) as a specific example, we derive a generic blueprint for how a holistic benchmark can be developed, which combines a specific scenario with a set of key performance indicators as metrics to evaluate the overall integrated system and its components.}, language = {de} } @inproceedings{NikolovskiLimpertNessauetal.2023, author = {Nikolovski, Gjorgji and Limpert, Nicolas and Nessau, Hendrik and Reke, Michael and Ferrein, Alexander}, title = {Model-predictive control with parallelised optimisation for the navigation of autonomous mining vehicles}, series = {2023 IEEE Intelligent Vehicles Symposium (IV)}, booktitle = {2023 IEEE Intelligent Vehicles Symposium (IV)}, publisher = {IEEE}, isbn = {979-8-3503-4691-6 (Online)}, doi = {10.1109/IV55152.2023.10186806}, pages = {6 Seiten}, year = {2023}, abstract = {The work in modern open-pit and underground mines requires the transportation of large amounts of resources between fixed points. The navigation to these fixed points is a repetitive task that can be automated. The challenge in automating the navigation of vehicles commonly used in mines is the systemic properties of such vehicles. Many mining vehicles, such as the one we have used in the research for this paper, use steering systems with an articulated joint bending the vehicle's drive axis to change its course and a hydraulic drive system to actuate axial drive components or the movements of tippers if available. To address the difficulties of controlling such a vehicle, we present a model-predictive approach for controlling the vehicle. While the control optimisation based on a parallel error minimisation of the predicted state has already been established in the past, we provide insight into the design and implementation of an MPC for an articulated mining vehicle and show the results of real-world experiments in an open-pit mine environment.}, language = {en} } @inproceedings{FerreinMaierMuehlbacheretal.2015, author = {Ferrein, Alexander and Maier, Christopher and M{\"u}hlbacher, Clemens and Niemueller, Tim and Steinbauer, Gerald and Vassos, Stravros}, title = {Controlling Logistics Robots with the Action-based Language YAGI}, series = {Proceedings of the 2015 IROS Workshop on Workshop on Task Planning for Intelligent Robots in Service and Manufacturing}, booktitle = {Proceedings of the 2015 IROS Workshop on Workshop on Task Planning for Intelligent Robots in Service and Manufacturing}, year = {2015}, 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{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{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{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{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{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{Ferrein2015, author = {Ferrein, Alexander}, title = {3D-Mapping von Straßentunneln}, series = {16. Geokinematischer Tag, 07. und 08. Mai 2015 : Tagungsband / Technische Universit{\"a}t Bergakademie Freiberg}, booktitle = {16. Geokinematischer Tag, 07. und 08. Mai 2015 : Tagungsband / Technische Universit{\"a}t Bergakademie Freiberg}, pages = {31 -- 40}, year = {2015}, language = {de} } @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{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{NiemuellerKarrasFerrein2017, author = {Niemueller, Tim and Karras, Ulrich and Ferrein, Alexander}, title = {Meisterschaft der Maschinen: Die Industrial Logistic Liga}, series = {C´t Magazin f{\"u}r Computertechnik}, journal = {C´t Magazin f{\"u}r Computertechnik}, number = {26}, year = {2017}, language = {de} } @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 = {International Harting Open Source Award 2016: Fawkes for the RoboCup Logistics League}, series = {RoboCup 2016: RoboCup 2016: Robot World Cup XX. RoboCup 2016}, booktitle = {RoboCup 2016: 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_53}, pages = {634 -- 642}, year = {2017}, language = {en} } @incollection{NiemuellerZwillingLakemeyeretal.2017, author = {Niemueller, Tim and Zwilling, Frederik and Lakemeyer, Gerhard and L{\"o}bach, Matthias and Reuter, Sebastian and Jeschke, Sabina and Ferrein, Alexander}, title = {Cyber-Physical System Intelligence}, series = {Industrial Internet of Things}, booktitle = {Industrial Internet of Things}, publisher = {Springer}, address = {Cham}, isbn = {978-3-319-42559-7}, doi = {10.1007/978-3-319-42559-7_17}, pages = {447 -- 472}, year = {2017}, abstract = {Cyber-physical systems are ever more common in manufacturing industries. Increasing their autonomy has been declared an explicit goal, for example, as part of the Industry 4.0 vision. To achieve this system intelligence, principled and software-driven methods are required to analyze sensing data, make goal-directed decisions, and eventually execute and monitor chosen tasks. In this chapter, we present a number of knowledge-based approaches to these problems and case studies with in-depth evaluation results of several different implementations for groups of autonomous mobile robots performing in-house logistics in a smart factory. We focus on knowledge-based systems because besides providing expressive languages and capable reasoning techniques, they also allow for explaining how a particular sequence of actions came about, for example, in the case of a failure.}, language = {en} } @inproceedings{KrueckelNoldenFerreinetal.2015, author = {Kr{\"u}ckel, Kai and Nolden, Florian and Ferrein, Alexander and Scholl, Ingrid}, title = {Intuitive visual teleoperation for UGVs using free-look augmented reality displays}, series = {2015 IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA}, booktitle = {2015 IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA}, doi = {10.1109/ICRA.2015.7139809}, pages = {4412 -- 4417}, year = {2015}, 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} } @article{ClaerFerreinSchiffer2019, author = {Claer, Mario and Ferrein, Alexander and Schiffer, Stefan}, title = {Calibration of a Rotating or Revolving Platform with a LiDAR Sensor}, series = {Applied Sciences}, volume = {Volume 9}, journal = {Applied Sciences}, number = {issue 11, 2238}, publisher = {MDPI}, address = {Basel}, issn = {2076-3417}, doi = {10.3390/app9112238}, pages = {18 Seiten}, year = {2019}, language = {en} } @inproceedings{MarcoFerrein2017, author = {Marco, Heather G. and Ferrein, Alexander}, title = {AGNES: The African-German Network of Excellence in Science}, series = {Proceedings of the 2nd Developing World Robotics Forum, Workshop at IEEE AFRICON 2017}, booktitle = {Proceedings of the 2nd Developing World Robotics Forum, Workshop at IEEE AFRICON 2017}, pages = {1 -- 2}, 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} } @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{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{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} } @incollection{HarlacherAltepostElsenetal.2024, author = {Harlacher, Markus and Altepost, Andrea and Elsen, Ingo and Ferrein, Alexander and Hansen-Ampah, Adjan and Merx, Wolfgang and Niehues, Sina and Schiffer, Stefan and Shahinfar, Fatemeh Nasim}, title = {Approach for the identification of requirements on the design of AI-supported work systems (in problem-based projects)}, series = {AI in Business and Economics}, booktitle = {AI in Business and Economics}, editor = {Lausberg, Isabel and Vogelsang, Michael}, publisher = {De Gruyter}, address = {Berlin}, isbn = {9783110790320}, doi = {10.1515/9783110790320}, pages = {87 -- 99}, year = {2024}, abstract = {To successfully develop and introduce concrete artificial intelligence (AI) solutions in operational practice, a comprehensive process model is being tested in the WIRKsam joint project. It is based on a methodical approach that integrates human, technical and organisational aspects and involves employees in the process. The chapter focuses on the procedure for identifying requirements for a work system that is implementing AI in problem-driven projects and for selecting appropriate AI methods. This means that the use case has already been narrowed down at the beginning of the project and must be completely defined in the following. Initially, the existing preliminary work is presented. Based on this, an overview of all procedural steps and methods is given. All methods are presented in detail and good practice approaches are shown. Finally, a reflection of the developed procedure based on the application in nine companies is given.}, language = {en} } @inproceedings{SchollBartellaMoluluoetal.2019, author = {Scholl, Ingrid and Bartella, Alexander K. 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} } @incollection{FerreinNikolovskiLimpertetal.2023, author = {Ferrein, Alexander and Nikolovski, Gjorgji and Limpert, Nicolas and Reke, Michael and Schiffer, Stefan and Scholl, Ingrid}, title = {Controlling a Fleet of Autonomous LHD Vehicles in Mining Operation}, series = {Multi-Robot Systems - New Advances}, booktitle = {Multi-Robot Systems - New Advances}, editor = {K{\"u}{\c{c}}{\"u}k, Serdar}, publisher = {Intech Open}, address = {London}, isbn = {978-1-83768-290-4}, doi = {10.5772/intechopen.113044}, pages = {21 Seiten}, year = {2023}, abstract = {In this chapter, we report on our activities to create and maintain a fleet of autonomous load haul dump (LHD) vehicles for mining operations. The ever increasing demand for sustainable solutions and economic pressure causes innovation in the mining industry just like in any other branch. In this chapter, we present our approach to create a fleet of autonomous special purpose vehicles and to control these vehicles in mining operations. After an initial exploration of the site we deploy the fleet. Every vehicle is running an instance of our ROS 2-based architecture. The fleet is then controlled with a dedicated planning module. We also use continuous environment monitoring to implement a life-long mapping approach. In our experiments, we show that a combination of synthetic, augmented and real training data improves our classifier based on the deep learning network Yolo v5 to detect our vehicles, persons and navigation beacons. The classifier was successfully installed on the NVidia AGX-Drive platform, so that the abovementioned objects can be recognised during the dumper drive. The 3D poses of the detected beacons are assigned to lanelets and transferred to an existing map.}, language = {de} }