@article{EngemannCoenenDawaretal.2021, author = {Engemann, Heiko and C{\"o}nen, Patrick and Dawar, Harshal and Du, Shengzhi and Kallweit, Stephan}, title = {A robot-assisted large-scale inspection of wind turbine blades in manufacturing using an autonomous mobile manipulator}, series = {Applied Sciences}, volume = {11}, journal = {Applied Sciences}, number = {19}, publisher = {MDPI}, address = {Basel}, issn = {2076-3417}, doi = {10.3390/app11199271}, pages = {1 -- 22}, year = {2021}, abstract = {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.}, 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} } @incollection{EngemannDuKallweitetal.2020, author = {Engemann, Heiko and Du, Shengzhi and Kallweit, Stephan and Ning, Chuanfang and Anwar, Saqib}, title = {AutoSynPose: Automatic Generation of Synthetic Datasets for 6D Object Pose Estimation}, series = {Machine Learning and Artificial Intelligence. Proceedings of MLIS 2020}, booktitle = {Machine Learning and Artificial Intelligence. Proceedings of MLIS 2020}, publisher = {IOS Press}, address = {Amsterdam}, isbn = {978-1-64368-137-5}, doi = {10.3233/FAIA200770}, pages = {89 -- 97}, year = {2020}, abstract = {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.}, language = {en} } @article{KunkelGebhardtMpofuetal.2019, author = {Kunkel, Maximilian Hugo and Gebhardt, Andreas and Mpofu, Khumbulani and Kallweit, Stephan}, title = {Quality assurance in metal powder bed fusion via deep-learning-based image classification}, series = {Rapid Prototyping Journal}, volume = {26}, journal = {Rapid Prototyping Journal}, number = {2}, issn = {1355-2546}, doi = {10.1108/RPJ-03-2019-0066}, pages = {259 -- 266}, year = {2019}, language = {en} } @article{FrankoDuKallweitetal.2020, author = {Franko, Josef and Du, Shengzhi and Kallweit, Stephan and Duelberg, Enno Sebastian and Engemann, Heiko}, title = {Design of a Multi-Robot System for Wind Turbine Maintenance}, series = {Energies}, volume = {13}, journal = {Energies}, number = {10}, publisher = {MDPI}, address = {Basel}, issn = {1996-1073}, doi = {10.3390/en13102552}, pages = {Article 2552}, year = {2020}, abstract = {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.}, language = {en} } @inproceedings{EngemannBadriWenningetal.2019, author = {Engemann, Heiko and Badri, Sriram and Wenning, Marius and Kallweit, Stephan}, title = {Implementation of an Autonomous Tool Trolley in a Production Line}, series = {Advances in Service and Industrial Robotics. RAAD 2019. Advances in Intelligent Systems and Computing, vol 980}, booktitle = {Advances in Service and Industrial Robotics. RAAD 2019. Advances in Intelligent Systems and Computing, vol 980}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-19648-6}, doi = {10.1007/978-3-030-19648-6_14}, pages = {117 -- 125}, year = {2019}, 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{FerreinSchifferKallweit2018, author = {Ferrein, Alexander and Schiffer, Stefan and Kallweit, Stephan}, title = {The ROSIN Education Concept - Fostering ROS Industrial-Related Robotics Education in Europe}, series = {ROBOT 2017: Third Iberian Robotics Conference}, booktitle = {ROBOT 2017: Third Iberian Robotics Conference}, publisher = {Springer}, address = {Cham}, isbn = {978-3-319-70836-2}, doi = {10.1007/978-3-319-70836-2_31}, pages = {370 -- 381}, year = {2018}, language = {en} } @article{MichauxMatternKallweit2018, author = {Michaux, F. and Mattern, P. and Kallweit, Stephan}, title = {RoboPIV: how robotics enable PIV on a large industrial scale}, series = {Measurement Science and Technology}, volume = {29}, journal = {Measurement Science and Technology}, number = {7}, publisher = {IOP}, address = {Bristol}, issn = {1361-6501}, doi = {10.1088/1361-6501/aab5c1}, pages = {074009}, year = {2018}, abstract = {This work demonstrates how the interaction between particle image velocimetry (PIV) and robotics can massively increase measurement efficiency. The interdisciplinary approach is shown using the complex example of an automated, large scale, industrial environment: a typical automotive wind tunnel application. Both the high degree of flexibility in choosing the measurement region and the complete automation of stereo PIV measurements are presented. The setup consists of a combination of three robots, individually used as a 6D traversing unit for the laser illumination system as well as for each of the two cameras. Synchronised movements in the same reference frame are realised through a master-slave setup with a single interface to the user. By integrating the interface into the standard wind tunnel management system, a single measurement plane or a predefined sequence of several planes can be requested through a single trigger event, providing the resulting vector fields within minutes. In this paper, a brief overview on the demands of large scale industrial PIV and the existing solutions is given. Afterwards, the concept of RoboPIV is introduced as a new approach. In a first step, the usability of a selection of commercially available robot arms is analysed. The challenges of pose uncertainty and importance of absolute accuracy are demonstrated through comparative measurements, explaining the individual pros and cons of the analysed systems. Subsequently, the advantage of integrating RoboPIV directly into the existing wind tunnel management system is shown on basis of a typical measurement sequence. In a final step, a practical measurement procedure, including post-processing, is given by using real data and results. Ultimately, the benefits of high automation are demonstrated, leading to a drastic reduction in necessary measurement time compared to non-automated systems, thus massively increasing the efficiency of PIV measurements.}, language = {en} } @article{KunkelGebhardtMpofuetal.2018, author = {Kunkel, Maximilian Hugo and Gebhardt, Andreas and Mpofu, Khumbaulani and Kallweit, Stephan}, title = {Statistical assessment of mechanical properties of selective laser melted specimens of stainless steel}, series = {The International Journal of Advanced Manufacturing Technology}, volume = {98}, journal = {The International Journal of Advanced Manufacturing Technology}, number = {5-8}, publisher = {Springer}, address = {London}, issn = {0268-3768}, doi = {10.1007/s00170-018-2040-8}, pages = {1409 -- 1431}, year = {2018}, abstract = {The rail business is challenged by long product life cycles and a broad spectrum of assembly groups and single parts. When spare part obsolescence occurs, quick solutions are needed. A reproduction of obsolete parts is often connected to long waiting times and minimum lot quantities that need to be purchased and stored. Spare part storage is therefore challenged by growing stocks, bound capital and issues of part ageing. A possible solution could be a virtual storage of spare parts which will be 3D printed through additive manufacturing technologies in case of sudden demand. As mechanical properties of additive manufactured parts are neither guaranteed by machine manufacturers nor by service providers, the utilization of this relatively young technology is impeded and research is required to address these issues. This paper presents an examination of mechanical properties of specimens manufactured from stainless steel through the selective laser melting (SLM) process. The specimens were produced in multiple batches. This paper interrogates the question if the test results follow a normal distribution pattern and if mechanical property predictions can be made. The results will be put opposite existing threshold values provided as the industrial standard. Furthermore, probability predictions will be made in order to examine the potential of the SLM process to maintain state-of-the-art mechanical property requirements.}, language = {en} }