TY - CHAP A1 - Ferrein, Alexander A1 - Maier, Christopher A1 - Mühlbacher, Clemens A1 - Niemüller, Tim A1 - Steinbauer, Gerald A1 - Vassos, Stravros T1 - Controlling logistics robots with the action-based language YAGI T2 - Intelligent Robotics and Applications: 9th International Conference, ICIRA 2016, Tokyo, Japan, August 22-24, 2016, Proceedings, Part I Y1 - 2016 SN - 978-3-319-43505-3 (Print) SN - 978-3-319-43506-0 (Online) U6 - https://doi.org/10.1007/978-3-319-43506-0_46 N1 - Series: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) VL - 9834 SP - 525 EP - 537 PB - Springer ER - TY - CHAP A1 - Braun, Carsten A1 - Boucke, Alexander A1 - Ballmann, Josef T1 - Numerical prediction of the wing deformation of a high speed transport aircraft type wind tunnel model by direct aeroelastic simulation T2 - Conference proceedings : CEAS/AIAA/DGLR International Forum on Aeroelasticity and Structural Dynamics IFASD 2005 : München, June 28 - July 1, 2005. DGLR-Bericht. 2005,04 Y1 - 2005 SN - 3-932182-43-X PB - DGLR CY - Bonn ER - TY - CHAP A1 - Niemueller, Tim A1 - Ferrein, Alexander A1 - Reuter, Sebastian A1 - Jeschke, Sabina A1 - Lakemeyer, Gerhard T1 - The RoboCup Logistics League as a Holistic Multi-Robot Smart Factory Benchmark T2 - Proceedings of the IROS 2015 Open forum on evaluation of results, replication of experiments and benchmarking in robotics research N2 - With autonomous mobile robots receiving increased attention in industrial contexts, the need for benchmarks becomes more and more an urgent matter. The RoboCup Logistics League (RCLL) is one specific industry-inspired scenario focusing on production logistics within a Smart Factory. In this paper, we describe how the RCLL allows to assess the performance of a group of robots within the scenario as a whole, focusing specifically on the coordination and cooperation strategies and the methods and components to achieve them. We report on recent efforts to analyze performance of teams in 2014 to understand the implications of the current grading scheme, and derived criteria and metrics for performance assessment based on Key Performance Indicators (KPI) adapted from classic factory evaluation. We reflect on differences and compatibility towards RoCKIn, a recent major benchmarking European project. Y1 - 2015 ER - TY - CHAP A1 - Eichenbaum, Julian A1 - Nikolovski, Gjorgji A1 - Mülhens, Leon A1 - Reke, Michael A1 - Ferrein, Alexander A1 - Scholl, Ingrid T1 - Towards a lifelong mapping approach using Lanelet 2 for autonomous open-pit mine operations T2 - 2023 IEEE 19th International Conference on Automation Science and Engineering (CASE) N2 - Autonomous agents require rich environment models for fulfilling their missions. High-definition maps are a well-established map format which allows for representing semantic information besides the usual geometric information of the environment. These are, for instance, road shapes, road markings, traffic signs or barriers. The geometric resolution of HD maps can be as precise as of centimetre level. In this paper, we report on our approach of using HD maps as a map representation for autonomous load-haul-dump vehicles in open-pit mining operations. As the mine undergoes constant change, we also need to constantly update the map. Therefore, we follow a lifelong mapping approach for updating the HD maps based on camera-based object detection and GPS data. We show our mapping algorithm based on the Lanelet 2 map format and show our integration with the navigation stack of the Robot Operating System. We present experimental results on our lifelong mapping approach from a real open-pit mine. Y1 - 2023 SN - 979-8-3503-2069-5 (Online) SN - 979-8-3503-2070-1 (Print) U6 - https://doi.org/10.1109/CASE56687.2023.10260526 N1 - 19th International Conference on Automation Science and Engineering (CASE), 26-30 August 2023, Auckland, New Zealand. PB - IEEE ER - TY - CHAP A1 - Niemueller, Tim A1 - Reuter, Sebastian A1 - Ewert, Daniel A1 - Ferrein, Alexander A1 - Jeschke, Sabina A1 - Lakemeyer, Gerhard ED - Almeida, Luis T1 - The Carologistics Approach to Cope with the Increased Complexity and New Challenges of the RoboCup Logistics League 2015 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_4 N1 - Lecture Notes in Computer Science ; 9513 SP - 47 EP - 59 PB - Springer International Publishing CY - Cham ER - TY - CHAP A1 - Konstantinidis, K. A1 - Kowalski, Julia A1 - Martinez, C. F. A1 - Dachwald, Bernd A1 - Ewerhart, D. A1 - Förstner, R. T1 - Some necessary technologies for in-situ astrobiology on enceladus T2 - Proceedings of the International Astronautical Congress Y1 - 2015 SN - 978-151081893-4 N1 - 6th International Astronautical Congress 2015: Space - The Gateway for Mankind's Future, IAC 2015; Jerusalem; Israel; 12 October 2015 through 16 October 2015 SP - 1354 EP - 1372 ER - TY - CHAP A1 - Dachwald, Bernd T1 - Low-Thrust Mission Analysis and Global Trajectory Optimization Using Evolutionary Neurocontrol: New Results T2 - European Workshop on Space Mission Analysis ESA/ESOC, Darmstadt, Germany 10 { 12 Dec 2007 N2 - Interplanetary trajectories for low-thrust spacecraft are often characterized by multiple revolutions around the sun. Unfortunately, the convergence of traditional trajectory optimizers that are based on numerical optimal control methods depends strongly on an adequate initial guess for the control function (if a direct method is used) or for the starting values of the adjoint vector (if an indirect method is used). Especially when many revolutions around the sun are re- quired, trajectory optimization becomes a very difficult and time-consuming task that involves a lot of experience and expert knowledge in astrodynamics and optimal control theory, because an adequate initial guess is extremely hard to find. Evolutionary neurocontrol (ENC) was proposed as a smart method for low-thrust trajectory optimization that fuses artificial neural networks and evolutionary algorithms to so-called evolutionary neurocontrollers (ENCs) [1]. Inspired by natural archetypes, ENC attacks the trajectoryoptimization problem from the perspective of artificial intelligence and machine learning, a perspective that is quite different from that of optimal control theory. Within the context of ENC, a trajectory is regarded as the result of a spacecraft steering strategy that maps permanently the actual spacecraft state and the actual target state onto the actual spacecraft control vector. This way, the problem of searching the optimal spacecraft trajectory is equivalent to the problem of searching (or "learning") the optimal spacecraft steering strategy. An artificial neural network is used to implement such a spacecraft steering strategy. It can be regarded as a parameterized function (the network function) that is defined by the internal network parameters. Therefore, each distinct set of network parameters defines a different network function and thus a different steering strategy. The problem of searching the optimal steering strategy is now equivalent to the problem of searching the optimal set of network parameters. Evolutionary algorithms that work on a population of (artificial) chromosomes are used to find the optimal network parameters, because the parameters can be easily mapped onto a chromosome. The trajectory optimization problem is solved when the optimal chromosome is found. A comparison of solar sail trajectories that have been published by others [2, 3, 4, 5] with ENC-trajectories has shown that ENCs can be successfully applied for near-globally optimal spacecraft control [1, 6] and that they are able to find trajectories that are closer to the (unknown) global optimum, because they explore the trajectory search space more exhaustively than a human expert can do. The obtained trajectories are fairly accurate with respect to the terminal constraint. If a more accurate trajectory is required, the ENC-solution can be used as an initial guess for a local trajectory optimization method. Using ENC, low-thrust trajectories can be optimized without an initial guess and without expert attendance. Here, new results for nuclear electric spacecraft and for solar sail spacecraft are presented and it will be shown that ENCs find very good trajectories even for very difficult problems. Trajectory optimization results are presented for 1. NASA's Solar Polar Imager Mission, a mission to attain a highly inclined close solar orbit with a solar sail [7] 2. a mission to de ect asteroid Apophis with a solar sail from a retrograde orbit with a very-high velocity impact [8, 9] 3. JPL's \2nd Global Trajectory Optimization Competition", a grand tour to visit four asteroids from different classes with a NEP spacecraft Y1 - 2007 ER - TY - CHAP A1 - Loeb, Horst W. A1 - Schartner, Karl-Heinz A1 - Seboldt, Wolfgang A1 - Dachwald, Bernd A1 - Streppel, Joern A1 - Meusemann, Hans A1 - Schülke, Peter T1 - SEP for a lander mission to the jovian moon europa T2 - 57th International Astronautical Congress N2 - Under DLR-contract, Giessen University and DLR Cologne are studying solar-electric propulsion missions (SEP) to the outer regions of the solar system. The most challenging reference mission concerns the transport of a 1.35-tons chemical lander spacecraft into an 80-RJ circular orbit around Jupiter, which would enable to place a 375 kg lander with 50 kg of scientific instruments on the surface of the icy moon "Europa". Thorough analyses show that the best solution in terms of SEP launch mass times thrusting time would be a two-stage EP module and a triple-junction solar array with concentrators which would be deployed step by step. Mission performance optimizations suggest to propel the spacecraft in the first EP stage by 6 gridded ion thrusters, running at 4.0 kV of beam voltage, which would save launch mass, and in the second stage by 4 thrusters with 1.25 to 1.5 kV of positive high voltage saving thrusting time. In this way, the launch mass of the spacecraft would be kept within 5.3 tons. Without a launcher's C3 and interplanetary gravity assists, Jupiter might be reached within about 4 yrs. The spiraling-down into the parking orbit would need another 1.8 yrs. This "large mission" can be scaled down to a smaller one, e.g., by halving all masses, the solar array power, and the number of thrusters. Due to their reliability, long lifetime and easy control, RIT-22 engines have been chosen for mission analysis. Based on precise tests, the thruster performance has been modeled. Y1 - 2006 U6 - https://doi.org/10.2514/6.IAC-06-C4.4.04 N1 - 57th International Astronautical Congress, 02 October 2006 - 06 October 2006, Valencia, Spain. SP - 1 EP - 12 ER - TY - CHAP A1 - Valero, Daniel A1 - Vogel, Jochen A1 - Schmidt, Daniel A1 - Bung, Daniel Bernhard T1 - Three-dimensional flow structure inside the cavity of a non-aerated stepped chute T2 - 7th IAHR International Symposium on Hydraulic Structures, Aachen, Germany, 15-18 May Y1 - 2018 SN - 978-0-692-13277-7 U6 - https://doi.org/10.15142/T3GH17 ER - TY - CHAP A1 - Anthrakidis, Anette A1 - Rusack, Markus A1 - Schwarzer, Klemens T1 - Low effort measurement method of PTC-efficiency T2 - SolarPACES 2010 : the CSP conference: electricity, fuels and clean water from concentrated solar energy ; 21 to 24 September 2010, Perpignan, France Y1 - 2010 SP - 48 EP - 49 PB - Soc. OSC CY - Saint Maur ER -