Dokument-ID Dokumenttyp Verfasser/Autoren Herausgeber Haupttitel Abstract Auflage Verlagsort Verlag Erscheinungsjahr Seitenzahl Schriftenreihe Titel Schriftenreihe Bandzahl ISBN Quelle der Hochschulschrift Konferenzname Bemerkung Quelle:Titel Quelle:Jahrgang Quelle:Heftnummer Quelle:Erste Seite Quelle:Letzte Seite URN DOI Zugriffsart Link Abteilungen OPUS4-7716 Konferenzveröffentlichung Kallweit, Stephan, kallweit@fh-aachen.de; Schleupen, Josef, schleupen@fh-aachen.de; Dahmann, Peter, dahmann@fh-aachen.de; Bagheri, Mohsen, bagheri@fh-aachen.de; Engemann, Heiko, engemann@fh-aachen.de Entwicklung eines Kletterroboters zur Diagnose und Instandsetzung von Windenergieanlagen (SMART) München DIV Deutscher Industrieverlag GmbH 2016 271 Seiten : Illustrationen Automatisierung im Fokus von Industrie 4.0 : Tagungsband AALE 2016 ; 13. Fachkonferenz, Lübeck 978-3-8356-7312-0 AALE-Konferenz <13., 2016, Lübeck> 207 212 weltweit http://doi.org/10.21269/7716 Fachbereich Luft- und Raumfahrttechnik OPUS4-7930 Konferenzveröffentlichung Schleupen, Josef, schleupen@fh-aachen.de; Engemann, Heiko, engemann@fh-aachen.de; Bagheri, Mohsen, bagheri@fh-aachen.de; Kallweit, Stephan, kallweit@fh-aachen.de; Dahmann, Peter, dahmann@fh-aachen.de Developing a climbing maintenance robot for tower and rotor blade service of wind turbines Cham Springer 2017 9 Advances in Robot Design and Intelligent Control : Proceedings of the 25th Conference on Robotics in Alpe-Adria-Danube Region (RAAD16) 978-3-319-49058-8 Advances in Robot Design and Intelligent Control ; Vol. 540 310 319 10.1007/978-3-319-49058-8_34 bezahl http://doi.org/10.1007/978-3-319-49058-8_34 Fachbereich Maschinenbau und Mechatronik OPUS4-8156 Konferenzveröffentlichung Engemann, Heiko, engemann@fh-aachen.de; Wiesen, Patrick, wiesen@fh-aachen.de; Kallweit, Stephan, kallweit@fh-aachen.de; Deshpande, Harshavardhan, ; Schleupen, Josef, schleupen@fh-aachen.de Autonomous mobile manipulation using ROS Cham Springer 2018 12 Advances in Service and Industrial Robotics 978-3-319-61276-8 International Conference on Robotics in Alpe-Adria Danube Region RAAD 2017; Mechanisms and Machince Science book series, Vol 49. 389 401 10.1007/978-3-319-61276-8_43 weltweit http://dx.doi.org/10.1007/978-3-319-61276-8_43 Fachbereich Maschinenbau und Mechatronik OPUS4-8277 Konferenzveröffentlichung Schleupen, Josef, schleupen@fh-aachen.de; Engemann, Heiko, engemann@fh-aachen.de; Bagheri, Mohsen, bagheri@fh-aachen.de; Kallweit, Stephan, kallweit@fh-aachen.de The potential of SMART climbing robot combined with a weatherproof cabin for rotor blade maintenance 2016 7 17th European Conference on Composite Materials – ECCM, Munich, Germany ECCM 17 1 8 weltweit https://www.researchgate.net/publication/310449913_THE_POTENTIAL_OF_SMART_CLIMBING_ROBOT_COMBINED_WITH_A_WEATHERPROOF_CABIN_FOR_ROTOR_BLADE_MAINTENANCE Fachbereich Luft- und Raumfahrttechnik OPUS4-8777 Konferenzveröffentlichung Wiesen, Patrick, wiesen@fh-aachen.de; Engemann, Heiko, engemann@fh-aachen.de; Limpert, Nicolas, limpert@fh-aachen.de; Kallweit, Stephan, kallweit@fh-aachen.de Learning by Doing - Mobile Robotics in the FH Aachen ROS Summer School 2018 12 Seiten European Robotics Forum 2018, TRROS18 Workshop 47 58 http://ceur-ws.org/Vol-2329/paper-06.pdf Fachbereich Maschinenbau und Mechatronik OPUS4-9508 Teil eines Buches Engemann, Heiko, engemann@fh-aachen.de; Du, Shengzhi, ; Kallweit, Stephan, kallweit@fh-aachen.de; Ning, Chuanfang, ; Anwar, Saqib, AutoSynPose: Automatic Generation of Synthetic Datasets for 6D Object Pose Estimation We present an automated pipeline for the generation of synthetic datasets for six-dimension (6D) object pose estimation. Therefore, a completely automated generation process based on predefined settings is developed, which enables the user to create large datasets with a minimum of interaction and which is feasible for applications with a high object variance. The pipeline is based on the Unreal 4 (UE4) game engine and provides a high variation for domain randomization, such as object appearance, ambient lighting, camera-object transformation and distractor density. In addition to the object pose and bounding box, the metadata includes all randomization parameters, which enables further studies on randomization parameter tuning. The developed workflow is adaptable to other 3D objects and UE4 environments. An exemplary dataset is provided including five objects of the Yale-CMU-Berkeley (YCB) object set. The datasets consist of 6 million subsegments using 97 rendering locations in 12 different UE4 environments. Each dataset subsegment includes one RGB image, one depth image and one class segmentation image at pixel-level. Amsterdam IOS Press 2020 8 Machine Learning and Artificial Intelligence. Proceedings of MLIS 2020 978-1-64368-137-5 Frontiers in Artificial Intelligence and Applications. Vol 332 89 97 10.3233/FAIA200770 weltweit https://doi.org/10.3233/FAIA200770 Fachbereich Maschinenbau und Mechatronik OPUS4-9513 Wissenschaftlicher Artikel Engemann, Heiko, engemann@fh-aachen.de; Du, Shengzhi, ; Kallweit, Stephan, kallweit@fh-aachen.de; Cönen, Patrick, coenen@fh-aachen.de; Dawar, Harshal, OMNIVIL - an autonomous mobile manipulator for flexible production Basel MDPI 2020 29 Sensors 20 1424-8220 Special issue: Sensor Networks Applications in Robotics and Mobile Systems 24, art. no. 7249 1 30 10.3390/s20247249 weltweit https://doi.org/10.3390/s20247249 Fachbereich Maschinenbau und Mechatronik OPUS4-8974 Konferenzveröffentlichung Engemann, Heiko, engemann@fh-aachen.de; Badri, Sriram, ; Wenning, Marius, ; Kallweit, Stephan, kallweit@fh-aachen.de Implementation of an Autonomous Tool Trolley in a Production Line Cham Springer 2019 8 Advances in Service and Industrial Robotics. RAAD 2019. Advances in Intelligent Systems and Computing, vol 980 978-3-030-19648-6 117 125 10.1007/978-3-030-19648-6_14 bezahl https://doi.org/10.1007/978-3-030-19648-6_14 Fachbereich Maschinenbau und Mechatronik OPUS4-9302 Wissenschaftlicher Artikel Franko, Josef, ; Du, Shengzhi, ; Kallweit, Stephan, kallweit@fh-aachen.de; Duelberg, Enno Sebastian, ; Engemann, Heiko, engemann@fh-aachen.de Design of a Multi-Robot System for Wind Turbine Maintenance The maintenance of wind turbines is of growing importance considering the transition to renewable energy. This paper presents a multi-robot-approach for automated wind turbine maintenance including a novel climbing robot. Currently, wind turbine maintenance remains a manual task, which is monotonous, dangerous, and also physically demanding due to the large scale of wind turbines. Technical climbers are required to work at significant heights, even in bad weather conditions. Furthermore, a skilled labor force with sufficient knowledge in repairing fiber composite material is rare. Autonomous mobile systems enable the digitization of the maintenance process. They can be designed for weather-independent operations. This work contributes to the development and experimental validation of a maintenance system consisting of multiple robotic platforms for a variety of tasks, such as wind turbine tower and rotor blade service. In this work, multicopters with vision and LiDAR sensors for global inspection are used to guide slower climbing robots. Light-weight magnetic climbers with surface contact were used to analyze structure parts with non-destructive inspection methods and to locally repair smaller defects. Localization was enabled by adapting odometry for conical-shaped surfaces considering additional navigation sensors. Magnets were suitable for steel towers to clamp onto the surface. A friction-based climbing ring robot (SMART— Scanning, Monitoring, Analyzing, Repair and Transportation) completed the set-up for higher payload. The maintenance period could be extended by using weather-proofed maintenance robots. The multi-robot-system was running the Robot Operating System (ROS). Additionally, first steps towards machine learning would enable maintenance staff to use pattern classification for fault diagnosis in order to operate safely from the ground in the future. Basel MDPI 2020 Energies 13 10 Article 2552 10.3390/en13102552 weltweit https://doi.org/10.3390/en13102552 Fachbereich Maschinenbau und Mechatronik OPUS4-9860 Wissenschaftlicher Artikel Engemann, Heiko, engemann@fh-aachen.de; Cönen, Patrick, coenen@fh-aachen.de; Dawar, Harshal, ; Du, Shengzhi, ; Kallweit, Stephan, kallweit@fh-aachen.de A robot-assisted large-scale inspection of wind turbine blades in manufacturing using an autonomous mobile manipulator Wind energy represents the dominant share of renewable energies. The rotor blades of a wind turbine are typically made from composite material, which withstands high forces during rotation. The huge dimensions of the rotor blades complicate the inspection processes in manufacturing. The automation of inspection processes has a great potential to increase the overall productivity and to create a consistent reliable database for each individual rotor blade. The focus of this paper is set on the process of rotor blade inspection automation by utilizing an autonomous mobile manipulator. The main innovations include a novel path planning strategy for zone-based navigation, which enables an intuitive right-hand or left-hand driving behavior in a shared human-robot workspace. In addition, we introduce a new method for surface orthogonal motion planning in connection with large-scale structures. An overall execution strategy controls the navigation and manipulation processes of the long-running inspection task. The implemented concepts are evaluated in simulation and applied in a real-use case including the tip of a rotor blade form. Basel MDPI 2021 21 Applied Sciences 11 Belongs to the Special Issue "Advances in Industrial Robotics and Intelligent Systems" 19 1 22 10.3390/app11199271 weltweit https://doi.org/10.3390/app11199271 Fachbereich Maschinenbau und Mechatronik