TY - CHAP A1 - Schleupen, Josef A1 - Engemann, Heiko A1 - Bagheri, Mohsen A1 - Kallweit, Stephan A1 - Dahmann, Peter T1 - Developing a climbing maintenance robot for tower and rotor blade service of wind turbines T2 - Advances in Robot Design and Intelligent Control : Proceedings of the 25th Conference on Robotics in Alpe-Adria-Danube Region (RAAD16) Y1 - 2017 SN - 978-3-319-49058-8 U6 - https://doi.org/10.1007/978-3-319-49058-8_34 N1 - Advances in Robot Design and Intelligent Control ; Vol. 540 SP - 310 EP - 319 PB - Springer CY - Cham ER - 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 - 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 - CHAP A1 - Ulmer, Jessica A1 - Braun, Sebastian A1 - Cheng, Chi-Tsun A1 - Dowey, Steve A1 - Wollert, Jörg T1 - Gamified Virtual Reality Training Environment for the Manufacturing Industry T2 - Proceedings of the 2020 19th International Conference on Mechatronics – Mechatronika (ME) N2 - 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. Y1 - 2020 U6 - https://doi.org/10.1109/ME49197.2020.9286661 N1 - 2020 19th International Conference on Mechatronics – Mechatronika (ME), Prague, Czech Republic, December 2–4, 2020 SP - 1 EP - 6 PB - IEEE CY - New York, NY 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 - 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 -