@incollection{KallweitGottschalkWalenta2016, author = {Kallweit, Stephan and Gottschalk, Michael and Walenta, Robert}, title = {ROS based safety concept for collaborative robots in industrial applications}, series = {Advances in robot design and intelligent control : proceedings of the 24th International Conference on Robotics in Alpe-Adria-Danube Region (RAAD). (Advances in intelligent systems and computing ; 371)}, booktitle = {Advances in robot design and intelligent control : proceedings of the 24th International Conference on Robotics in Alpe-Adria-Danube Region (RAAD). (Advances in intelligent systems and computing ; 371)}, publisher = {Springer}, address = {Cham}, organization = {International Conference on Robotics in Alpe-Adria-Danube Region <24, 2015, Bucharest>}, isbn = {978-3-319-21289-0 (Print) ; 978-3-319-21290-6 (E-Book)}, doi = {10.1007/978-3-319-21290-6_3}, pages = {27 -- 35}, year = {2016}, abstract = {The production and assembly of customized products increases the demand for flexible automation systems. One approach is to remove the safety fences that separate human and industrial robot to combine their skills. This collaboration possesses a certain risk for the human co-worker, leading to numerous safety concepts to protect him. The human needs to be monitored and tracked by a safety system using different sensors. The proposed system consists of a RGBD camera for surveillance of the common working area, an array of optical distance sensors to compensate shadowing effects of the RGBD camera and a laser range finder to detect the co-worker when approaching the work cell. The software for collision detection, path planning, robot control and predicting the behaviour of the co-worker is based on the Robot Operating System (ROS). A first prototype of the work cell shows that with advanced algorithms from the field of mobile robotics a very flexible safety concept can be realized: the robot not simply stops its movement when detecting a collision, but plans and executes an alternative path around the obstacle.}, language = {en} } @inproceedings{ChavezBermudezCruzCastanonRuchayetal.2022, author = {Chavez Bermudez, Victor Francisco and Cruz Castanon, Victor Fernando and Ruchay, Marco and Wollert, J{\"o}rg}, title = {Rapid prototyping framework for automation applications based on IO-Link}, series = {Tagungsband AALE 2022: Wissenstransfer im Spannungsfeld von Autonomisierung und Fachkr{\"a}ftemangel}, booktitle = {Tagungsband AALE 2022: Wissenstransfer im Spannungsfeld von Autonomisierung und Fachkr{\"a}ftemangel}, editor = {Leipzig, Hochschule f{\"u}r Technik, Wirtschaft und Kultur}, address = {Leipzig}, isbn = {978-3-910103-00-9}, doi = {10.33968/2022.28}, pages = {8 Seiten}, year = {2022}, abstract = {The development of protype applications with sensors and actuators in the automation industry requires tools that are independent of manufacturer, and are flexible enough to be modified or extended for any specific requirements. Currently, developing prototypes with industrial sensors and actuators is not straightforward. First of all, the exchange of information depends on the industrial protocol that these devices have. Second, a specific configuration and installation is done based on the hardware that is used, such as automation controllers or industrial gateways. This means that the development for a specific industrial protocol, highly depends on the hardware and the software that vendors provide. In this work we propose a rapid-prototyping framework based on Arduino to solve this problem. For this project we have focused to work with the IO-Link protocol. The framework consists of an Arduino shield that acts as the physical layer, and a software that implements the IO-Link Master protocol. The main advantage of such framework is that an application with industrial devices can be rapid-prototyped with ease as its vendor independent, open-source and can be ported easily to other Arduino compatible boards. In comparison, a typical approach requires proprietary hardware, is not easy to port to another system and is closed-source.}, language = {en} } @article{CollPeralesSchulteTiggesRondinoneetal.2022, author = {Coll-Perales, Baldomero and Schulte-Tigges, Joschua and Rondinone, Michele and Gozalvez, Javier and Reke, Michael and Matheis, Dominik and Walter, Thomas}, title = {Prototyping and evaluation of infrastructure-assisted transition of control for cooperative automated vehicles}, series = {IEEE Transactions on Intelligent Transportation Systems}, volume = {23}, journal = {IEEE Transactions on Intelligent Transportation Systems}, number = {7}, publisher = {IEEE}, issn = {1524-9050 (Print)}, doi = {10.1109/TITS.2021.3061085}, pages = {6720 -- 6736}, year = {2022}, abstract = {Automated driving is now possible in diverse road and traffic conditions. However, there are still situations that automated vehicles cannot handle safely and efficiently. In this case, a Transition of Control (ToC) is necessary so that the driver takes control of the driving. Executing a ToC requires the driver to get full situation awareness of the driving environment. If the driver fails to get back the control in a limited time, a Minimum Risk Maneuver (MRM) is executed to bring the vehicle into a safe state (e.g., decelerating to full stop). The execution of ToCs requires some time and can cause traffic disruption and safety risks that increase if several vehicles execute ToCs/MRMs at similar times and in the same area. This study proposes to use novel C-ITS traffic management measures where the infrastructure exploits V2X communications to assist Connected and Automated Vehicles (CAVs) in the execution of ToCs. The infrastructure can suggest a spatial distribution of ToCs, and inform vehicles of the locations where they could execute a safe stop in case of MRM. This paper reports the first field operational tests that validate the feasibility and quantify the benefits of the proposed infrastructure-assisted ToC and MRM management. The paper also presents the CAV and roadside infrastructure prototypes implemented and used in the trials. The conducted field trials demonstrate that infrastructure-assisted traffic management solutions can reduce safety risks and traffic disruptions.}, 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} } @article{EngemannDuKallweitetal.2020, author = {Engemann, Heiko and Du, Shengzhi and Kallweit, Stephan and C{\"o}nen, Patrick and Dawar, Harshal}, title = {OMNIVIL - an autonomous mobile manipulator for flexible production}, series = {Sensors}, volume = {20}, journal = {Sensors}, number = {24, art. no. 7249}, publisher = {MDPI}, address = {Basel}, isbn = {1424-8220}, doi = {10.3390/s20247249}, pages = {1 -- 30}, year = {2020}, language = {en} } @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} } @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{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} } @article{FerreinSteinbauer2016, author = {Ferrein, Alexander and Steinbauer, Gerald}, title = {Looking back on 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/s13218-016-0443-y}, pages = {321 -- 323}, year = {2016}, 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{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{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} } @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{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{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} } @article{ChengWollertChenetal.2023, author = {Cheng, Chi-Tsun and Wollert, J{\"o}rg and Chen, Xi and Fapojuwo, Abraham O.}, title = {Guest Editorial : Circuits and Systems for Industry X.0 Applications}, series = {IEEE Journal on Emerging and Selected Topics in Circuits and Systems}, volume = {13}, journal = {IEEE Journal on Emerging and Selected Topics in Circuits and Systems}, edition = {2}, publisher = {IEEE}, address = {New York}, issn = {2156-3357 (Print)}, doi = {10.1109/JETCAS.2023.3278843}, pages = {457 -- 460}, year = {2023}, 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{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{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} } @article{UlmerBraunChengetal.2022, author = {Ulmer, Jessica and Braun, Sebastian and Cheng, Chi-Tsun and Dowey, Steve and Wollert, J{\"o}rg}, title = {Gamification of virtual reality assembly training: Effects of a combined point and level system on motivation and training results}, series = {International Journal of Human-Computer Studies}, volume = {165}, journal = {International Journal of Human-Computer Studies}, number = {Art. No. 102854}, publisher = {Elsevier}, address = {Amsterdam}, issn = {1071-5819}, doi = {10.1016/j.ijhcs.2022.102854}, year = {2022}, abstract = {Virtual Reality (VR) offers novel possibilities for remote training regardless of the availability of the actual equipment, the presence of specialists, and the training locations. Research shows that training environments that adapt to users' preferences and performance can promote more effective learning. However, the observed results can hardly be traced back to specific adaptive measures but the whole new training approach. This study analyzes the effects of a combined point and leveling VR-based gamification system on assembly training targeting specific training outcomes and users' motivations. The Gamified-VR-Group with 26 subjects received the gamified training, and the Non-Gamified-VR-Group with 27 subjects received the alternative without gamified elements. Both groups conducted their VR training at least three times before assembling the actual structure. The study found that a level system that gradually increases the difficulty and error probability in VR can significantly lower real-world error rates, self-corrections, and support usages. According to our study, a high error occurrence at the highest training level reduced the Gamified-VR-Group's feeling of competence compared to the Non-Gamified-VR-Group, but at the same time also led to lower error probabilities in real-life. It is concluded that a level system with a variable task difficulty should be combined with carefully balanced positive and negative feedback messages. This way, better learning results, and an improved self-evaluation can be achieved while not causing significant impacts on the participants' feeling of competence.}, language = {en} }