Cyber-Physical Construction Platform

Research Project 8-1 (RP 8-1)

IntCDC Research Project 8-1 – Cyber-Physical Construction Platform
CYBER-PHYSICAL CONSTRUCTION PLATFORM

The aim of this research project is to develop a cyber-physical construction (CPC) platform for the automated and rope guided handling of heavy loads and the on-site assembly of prefabricated elements for multi-storey buildings. An automated tower crane, as a large workspace serving the handling system, realises the pick-up and transportation processes. Imaging methods or laser scanning is used to monitor all automated processes and the overall construction progress resulting in a construction site monitoring concept. With the aim of full automation, we will plan paths and trajectories for material transportation and assembly based on an environmental model derived from these sensors. The specific tasks to be automated will be derived from planning data of the construction process. To be able to compare the current state of the site with the planning data, a semantic interpretation will be added to the geometric information of the as-built 3D model.

We will develop a novel hook-mounted gripper system for the tower crane, to handle differently shaped elements. In addition, we aim to automatically perform coordinated motions of the tower crane and the spider crane, which is the subject of the research project Robotic Platform for Cyber-Physical Assembly (RP 16-1), in order to seamlessly place prefabricated elements. This will be achieved by developing hybrid control strategies.

PRINCIPAL INVESTIGATORS

Prof. Dr.-Ing. habil. Dr. h.c. Oliver Sawodny
Institute for System Dynamics (ISYS), University of Stuttgart
Prof. Dr.-Ing. Uwe Sörgel
Institute for Photogrammetry (IFP), University of Stuttgart

TEAM

apl. Prof. Dr.-Ing. Norbert Haala (IFP)
Mark Burkhardt (ISYS)
Lena Joachim (IFP)

PEER-REVIEWED PUBLICATIONS

  1. 2024

    1. Schüle, J., Burkhardt, M., Gienger, A., & Sawodny, O. (2024). Towards Automated Construction: Visual-based Pose Reconstruction for Tower Crane Operations using Differentiable Rendering and Network-based Image Segmentation. 2024 IEEE 33rd International Symposium on Industrial Electronics (ISIE), 1–7. https://doi.org/10.1109/ISIE54533.2024.10595817

  2. 2023

    1. Burkhardt, M., Gienger, A., Joachim, L., Haala, N., Sörgel, U., & Sawodny, O. (2023). Data-based error compensation for georeferenced payload path tracking of automated tower cranes. Mechatronics, 94, 103028--. https://doi.org/10.1016/j.mechatronics.2023.103028
    2. Burkhardt, M., Gienger, A., & Sawodny, O. (2023). Optimization-Based Multipoint Trajectory Planning Along Straight Lines for Tower Cranes. IEEE Transactions on Control Systems Technology, 1–8. https://doi.org/10.1109/TCST.2023.3308762
    3. Burkhardt, M., Joachim, L., Gienger, A., Haala, N., Sörgel, U., & Sawodny, O. (2023, August). Rotation Control of a Novel Crane Gripper with Visual-Inertial Feedback. Proceedings of 2023 IEEE 19th International Conference on Automation Science and Engineering (CASE).
    4. Collmar, D., Walter, V., Koelle, M., & Soergel, U. (2023). FROM MULTIPLE POLYGONS TO SINGLE GEOMETRY: OPTIMIZATION OF POLYGON INTEGRATION FOR CROWDSOURCED DATA. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, X-1/W1-2023, 159--166. https://doi.org/10.5194/isprs-annals-X-1-W1-2023-159-2023
    5. Haala, N., Zhang, W., Joachim, L., Skuddis, D., Abolhasani, S., Schwieger, V., & Soergel, U. (2023). Zum Potenzial von SLAM-Verfahren für geodätische Echtzeit-Messaufgaben. Allgemeine Vermessungsnachrichten (Avn), 163–172. https://gispoint.de/artikelarchiv/avn/2023/avn-ausgabe-052023/7879-zum-potenzial-von-slam-verfahren-fuer-geodaetische-echtzeit-messaufgaben.html
    6. Schneider, P. J., Yang, C.-H., Li, Y., Koppe, M., Soergel, U., Pakzad, K., & Rudolf, T. (2023). DEVELOPMENT OF A WEB PLATFORM TO VISUALIZE PS-INSAR DATA IN A BUILDING INFORMATION MANAGEMENT SYSTEM. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, X-1/W1-2023, 869--873. https://doi.org/10.5194/isprs-annals-X-1-W1-2023-869-2023
    7. Zhang, X., Lin, D., Xue, R., & Soergel, U. (2023). TARGET-GUIDED LEARNING FOR RARE CLASS SEGMENTATION IN LARGE-SCALE URBAN POINT CLOUDS. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLVIII-1/W2-2023, 1693--1698. https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-1693-2023

  3. 2022

    1. Burkhardt, M., Joachim, L., Lerke, O., Thomas, M., Schwieger, V., Haala, N., & Sawodny, O. (2022). Kran. Deutsches Patent- und Markenamt.
    2. Joachim, L., Zhang, W., Haala, N., & Soergel, U. (2022). Evaluation of the quality of real-time mapping with crane cameras and visual SLAM algorithms. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLIII-B2-2022, 545–552. https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-545-2022
    3. Thomas, M., & Sawodny, O. (2022). Flatness-based feedforward and modal model-predictive state-feedback control of a double pendulum bridge crane. The 9th IFAC Symposium on Mechatronic Systems & The 16th International Conference on Motion and Vibration Control, 24–29.
    4. Wolff, F., Uchiyama, N., Burkhardt, M., & Sawodny, O. (2022). Nonlinear Model Predictive Control with Non-Equidistant Discretization Time Grids for Rotary Cranes. 2022 13th Asian Control Conference (ASCC), 1753–1758. https://doi.org/10.23919/ASCC56756.2022.9828180

  4. 2021

    1. Burkhardt, M., & Sawodny, O. (2021). Towards Modeling and Control of a Crane-Collaboration for the Automated Assembly of Timber Structures. IECON 2021 - 47th Annual Conference of the IEEE Industrial Electronics Society, 1–6. https://doi.org/10.1109/IECON48115.2021.9589787
    2. Burkhardt, M., & Sawodny, O. (2021). A graph-based path planning algorithm for the control of tower cranes. 2021 American Control Conference (ACC), 1736–1741. https://doi.org/10.23919/ACC50511.2021.9482797
    3. Rauscher, F., & Sawodny, O. (2021). Efficient Online Trajectory Planning for Integrator Chain Dynamics using Polynomial Elimination. IEEE Robotics and Automation Letters, 6(3), Article 3. https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9403885
    4. Thomas, M., Werner, T., & Sawodny, O. (2021). Online trajectory generation and feedforward control for manually-driven cranes with input constraints. 2021 IEEE Conference on Control Technology and Applications (CCTA).

OTHER PUBLICATIONS

  1. 2023

    1. Burkhardt, M., Joachim, L., Gienger, A., Haala, N., Sörgel, U., & Sawodny, O. (2023). Datenbasiertes Korrektursystem für Lastpositionsfehler von automatisierten Turmdrehkranen in Absolutkoordinaten. Deutsches Patent- und Markenamt.
    2. Kölle, M., Walter, V., Shiller, I., & Soergel, U. (2023). Efficient and Accurate Tree Detection from 3D Point Clouds through Paid Crowdsourcing. https://doi.org/10.48550/arXiv.2308.14499

  2. 2022

    1. Ackermann, S., & Joachim, L. (2022). Simulation und Auswertung eines photogrammetrischen Bildverbandes aus Krankamerabildern. 42. Wissenschaftlich-Technische Jahrestagung Der DGPF, 297–303. https://doi.org/10.24407/KXP:1796047422

  3. 2021

    1. Joachim, L., Ackermann, S., Haala, N., & Soergel, U. (2021). Using Crane Cameras for Workspace Mapping and Monitoring for an Autonomous Tower Crane. Proceedings of the 7th International Conference on Machine Control & Guidance, 47–53. http://mobilearbeitsmaschine.de/downloads.html?file=files/MCG2021/MCG2021_Conference%20Proceedings_Web.pdf

    

To the top of the page