TY - CHAP A1 - Leingartner, Max A1 - Maurer, Johannes A1 - Steinbauer, Gerald A1 - Ferrein, Alexander T1 - Evaluation of sensors and mapping approaches for disasters in tunnels T2 - IEEE International Symposium on Safety, Security, and Rescue Robotics : SSRR : 21-26 Oct. 2013, Linkoping, Sweden Y1 - 2013 SN - 978-1-4799-0879-0 SP - 1 EP - 7 ER - TY - JOUR A1 - Leingartner, Max A1 - Maurer, Johannes A1 - Ferrein, Alexander A1 - Steinbauer, Gerald T1 - Evaluation of Sensors and Mapping Approaches for Disasters in Tunnels JF - Journal of Field Robotics N2 - Ground or aerial robots equipped with advanced sensing technologies, such as three-dimensional laser scanners and advanced mapping algorithms, are deemed useful as a supporting technology for first responders. A great deal of excellent research in the field exists, but practical applications at real disaster sites are scarce. Many projects concentrate on equipping robots with advanced capabilities, such as autonomous exploration or object manipulation. In spite of this, realistic application areas for such robots are limited to teleoperated reconnaissance or search. In this paper, we investigate how well state-of-the-art and off-the-shelf components and algorithms are suited for reconnaissance in current disaster-relief scenarios. The basic idea is to make use of some of the most common sensors and deploy some widely used algorithms in a disaster situation, and to evaluate how well the components work for these scenarios. We acquired the sensor data from two field experiments, one from a disaster-relief operation in a motorway tunnel, and one from a mapping experiment in a partly closed down motorway tunnel. Based on these data, which we make publicly available, we evaluate state-of-the-art and off-the-shelf mapping approaches. In our analysis, we integrate opinions and replies from first responders as well as from some algorithm developers on the usefulness of the data and the limitations of the deployed approaches, respectively. We discuss the lessons we learned during the two missions. These lessons are interesting for the community working in similar areas of urban search and rescue, particularly reconnaissance and search. Y1 - 2016 U6 - https://doi.org/10.1002/rob.21611 SN - 1556-4967 VL - 33 IS - 8 SP - 1037 EP - 1057 PB - Wiley-VCH CY - Weinheim ER - TY - CHAP A1 - Niemueller, Tim A1 - Reuter, Sebastian A1 - Ferrein, Alexander A1 - Jeschke, Sabina A1 - Lakemeyer, Gerhard ED - Almeida, Luis T1 - Evaluation of the RoboCup Logistics League and Derived Criteria for Future Competitions T2 - RoboCup 2015: Robot World Cup XIX Y1 - 2016 SN - 978-3-319-29339-4 U6 - https://doi.org/10.1007/978-3-319-29339-4_3 N1 - Lecture Notes in Computer Science ; 9513 SP - 31 EP - 43 PB - Springer International Publishing CY - Cham ER - TY - CHAP A1 - Niemueller, Tim A1 - Reuter, Sebastian A1 - Ferrein, Alexander ED - Almeida, Luis T1 - Fawkes for the RoboCup Logistics League T2 - RoboCup 2015: Robot World Cup XIX Y1 - 2016 SN - 978-3-319-29339-4 U6 - https://doi.org/10.1007/978-3-319-29339-4_31 N1 - Lecture Notes in Computer Science ; 9513 SP - 365 EP - 373 PB - Springer International Publishing CY - Cham ER - TY - JOUR A1 - Ulmer, Jessica A1 - Braun, Sebastian A1 - Cheng, Chi-Tsun A1 - Dowey, Steve A1 - Wollert, Jörg T1 - Gamification of virtual reality assembly training: Effects of a combined point and level system on motivation and training results JF - International Journal of Human-Computer Studies N2 - 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. KW - Gamification KW - Virtual reality KW - Assembly KW - User study KW - Level system Y1 - 2022 U6 - https://doi.org/10.1016/j.ijhcs.2022.102854 SN - 1071-5819 VL - 165 IS - Art. No. 102854 PB - Elsevier CY - Amsterdam ER - TY - CHAP A1 - Mataré, Victor A1 - Schiffer, Stefan A1 - Ferrein, Alexander ED - Steinbauer, Gerald ED - Ferrein, Alexander T1 - golog++ : An integrative system design T2 - 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 Y1 - 2019 SN - 1613-0073 SP - 29 EP - 35 ER - TY - CHAP A1 - Chajan, Eduard A1 - Schulte-Tigges, Joschua A1 - Reke, Michael A1 - Ferrein, Alexander A1 - Matheis, Dominik A1 - Walter, Thomas T1 - GPU based model-predictive path control for self-driving vehicles T2 - IEEE Intelligent Vehicles Symposium (IV) N2 - 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. KW - Heuristic algorithms KW - Computational modeling KW - model-predictive control KW - GPU KW - autonomous driving Y1 - 2021 SN - 978-1-7281-5394-0 U6 - https://doi.org/10.1109/IV48863.2021.9575619 N1 - 2021 IEEE Intelligent Vehicles Symposium (IV), July 11-17, 2021. Nagoya, Japan SP - 1243 EP - 1248 PB - IEEE CY - New York, NY ER - TY - JOUR A1 - Cheng, Chi-Tsun A1 - Wollert, Jörg A1 - Chen, Xi A1 - Fapojuwo, Abraham O. T1 - Guest Editorial : Circuits and Systems for Industry X.0 Applications JF - IEEE Journal on Emerging and Selected Topics in Circuits and Systems Y1 - 2023 U6 - https://doi.org/10.1109/JETCAS.2023.3278843 SN - 2156-3357 (Print) SN - 2156-3365 (Online) VL - 13 SP - 457 EP - 460 PB - IEEE CY - New York ET - 2 ER - TY - CHAP A1 - Niemueller, Tim A1 - Neumann, Tobias A1 - Henke, Christoph A1 - Schönitz, Sebastian A1 - Reuter, Sebastian A1 - Ferrein, Alexander A1 - Jeschke, Sabina A1 - Lakemeyer, Gerhard T1 - Improvements for a robust production in the RoboCup logistics league 2016 T2 - RoboCup 2016: Robot World Cup XX. RoboCup 2016. Y1 - 2017 SN - 978-3-319-68792-6 U6 - https://doi.org/10.1007/978-3-319-68792-6_49 SP - 589 EP - 600 PB - Springer CY - Cham ER - TY - CHAP A1 - Alhwarin, Faraj A1 - Ferrein, Alexander A1 - Gebhardt, Andreas A1 - Kallweit, Stephan A1 - Scholl, Ingrid A1 - Tedjasukmana, Osmond Sanjaya T1 - Improving additive manufacturing by image processing and robotic milling T2 - 2015 IEEE International Conference on Automation Science and Engineering (CASE), Aug 24-28, 2015 Gothenburg, Sweden Y1 - 2015 U6 - https://doi.org/10.1109/CoASE.2015.7294217 SP - 924 EP - 929 ER - TY - CHAP A1 - Kirsch, Maximilian A1 - Mataré, Victor A1 - Ferrein, Alexander A1 - Schiffer, Stefan T1 - Integrating golog++ and ROS for Practical and Portable High-level Control T2 - Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 2 N2 - 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. Y1 - 2020 U6 - https://doi.org/10.5220/0008984406920699 N1 - Proceedings of the 12th International Conference on Agents and Artificial Intelligence: ICAART 2020, Valletta, Malta SP - 692 EP - 699 PB - SciTePress CY - Setúbal, Portugal ER - TY - CHAP A1 - Niemueller, Tim A1 - Neumann, Tobias A1 - Henke, Christoph A1 - Schönitz, Sebastian A1 - Reuter, Sebastian A1 - Ferrein, Alexander A1 - Jeschke, Sabina A1 - Lakemeyer, Gerhard T1 - International Harting Open Source Award 2016: Fawkes for the RoboCup Logistics League T2 - RoboCup 2016: RoboCup 2016: Robot World Cup XX. RoboCup 2016 Y1 - 2017 SN - 978-3-319-68792-6 U6 - https://doi.org/10.1007/978-3-319-68792-6_53 N1 - Lecture Notes in Computer Science, LNCS, Vol 9776 SP - 634 EP - 642 PB - Springer CY - Cham ER - TY - CHAP A1 - Krückel, Kai A1 - Nolden, Florian A1 - Ferrein, Alexander A1 - Scholl, Ingrid T1 - Intuitive visual teleoperation for UGVs using free-look augmented reality displays T2 - 2015 IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA Y1 - 2015 U6 - https://doi.org/10.1109/ICRA.2015.7139809 SP - 4412 EP - 4417 ER - TY - CHAP A1 - Wiesen, Patrick A1 - Engemann, Heiko A1 - Limpert, Nicolas A1 - Kallweit, Stephan T1 - Learning by Doing - Mobile Robotics in the FH Aachen ROS Summer School T2 - European Robotics Forum 2018, TRROS18 Workshop Y1 - 2018 SP - 47 EP - 58 ER - TY - JOUR A1 - Ferrein, Alexander A1 - Steinbauer, Gerald T1 - Looking back on 20 Years of RoboCup JF - KI - Künstliche Intelligenz Y1 - 2016 U6 - https://doi.org/10.1007/s13218-016-0443-y SN - 1610-1987 VL - 30 IS - 3-4 SP - 321 EP - 323 PB - Springer CY - Berlin ER - TY - CHAP A1 - Scholl, Ingrid A1 - Bartella, Alex A1 - Moluluo, Cem A1 - Ertural, Berat A1 - Laing, Frederic A1 - Suder, Sebastian T1 - MedicVR : Acceleration and Enhancement Techniques for Direct Volume Rendering in Virtual Reality T2 - Bildverarbeitung für die Medizin 2019 : Algorithmen – Systeme – Anwendungen Y1 - 2019 SN - 978-3-658-25326-4 U6 - https://doi.org/10.1007/978-3-658-25326-4_32 SP - 152 EP - 157 PB - Springer Vieweg CY - Wiesbaden ER - TY - CHAP A1 - Nikolovski, Gjorgji A1 - Limpert, Nicolas A1 - Nessau, Hendrik A1 - Reke, Michael A1 - Ferrein, Alexander T1 - Model-predictive control with parallelised optimisation for the navigation of autonomous mining vehicles T2 - 2023 IEEE Intelligent Vehicles Symposium (IV) N2 - 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. KW - Mpc KW - Control KW - Path-following KW - Navigation KW - Automation Y1 - 2023 SN - 979-8-3503-4691-6 (Online) SN - 979-8-3503-4692-3 (Print) U6 - https://doi.org/10.1109/IV55152.2023.10186806 N1 - IEEE Symposium on Intelligent Vehicle, 4.-7. June 2023, Anchorage, AK, USA. PB - IEEE ER - TY - JOUR A1 - Engemann, Heiko A1 - Du, Shengzhi A1 - Kallweit, Stephan A1 - Cönen, Patrick A1 - Dawar, Harshal T1 - OMNIVIL - an autonomous mobile manipulator for flexible production JF - Sensors Y1 - 2020 SN - 1424-8220 U6 - https://doi.org/10.3390/s20247249 N1 - Special issue: Sensor Networks Applications in Robotics and Mobile Systems VL - 20 IS - 24, art. no. 7249 SP - 1 EP - 30 PB - MDPI CY - Basel ER - TY - JOUR A1 - Braun, Sebastian A1 - Cheng, Chi-Tsun A1 - Dowey, Steve A1 - Wollert, Jörg T1 - Performance evaluation of skill-based order-assignment in production environments with multi-agent systems JF - IEEE Journal of Emerging and Selected Topics in Industrial Electronics N2 - 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. KW - cyber-physical production systems KW - event-based simulation KW - multi-agent systems KW - digital factory KW - industrial agents Y1 - 2021 U6 - https://doi.org/10.1109/JESTIE.2021.3108524 SN - 2687-9735 IS - Early Access PB - IEEE CY - New York ER - TY - JOUR A1 - Coll-Perales, Baldomero A1 - Schulte-Tigges, Joschua A1 - Rondinone, Michele A1 - Gozalvez, Javier A1 - Reke, Michael A1 - Matheis, Dominik A1 - Walter, Thomas T1 - Prototyping and evaluation of infrastructure-assisted transition of control for cooperative automated vehicles JF - IEEE Transactions on Intelligent Transportation Systems N2 - 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. KW - Automated driving KW - automated vehicles KW - connected automated vehicles KW - CAV KW - experimental evaluation Y1 - 2021 U6 - https://doi.org/10.1109/TITS.2021.3061085 SN - 1524-9050 (Print) SN - 1558-0016 (Online) VL - 23 IS - 7 SP - 6720 EP - 6736 PB - IEEE ER -