Cyber-Physical Construction Platform

Research Project 8-1 (RP 8-1)

CYBER-PHYSICAL CONSTRUCTION PLATFORM

This research project addresses the development of a cyber-physical construction (CPC) platform for automated and rope guided handling of heavy loads and on-site assembly of prefabricated elements for multi-storey buildings. An automated tower crane realizes pick up and transportation processes as a large workspace serving handling system. Imaging methods or laser scanning will be applied to monitor all automated processes and the overall construction progress resulting in a construction site monitoring concept. Aiming at 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 that shall be executed automatically 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.

In order to handle different shaped elements, we will develop a novel hook-mounted gripper system for the tower crane. Additionally, we aim at the automatic execution of coordinated motions of the tower crane and the spider crane covered by Research Project 16 in order to seamlessly place prefabricated elements. This is achieved through the development of hybrid control strategies.

 

PRINCIPAL INVESTIGATORS

Prof. Dr.-Ing. 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. 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. 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

  3. 2021

    1. Burkhardt, M., & Sawodny, O. (2021). Towards Modeling and Control of a Crane-Collaboration for the Automated Assembly of Timber Structures. Proceedings of the 47th Annual Conference of the IEEE IES (IECON).
    2. Burkhardt, M., & Sawodny, O. (2021). A Graph-Based Path Planning Algorithm for the Control of Tower Cranes. 2021 American Control Conference (ACC).
    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. 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

  2. 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

DATA SETS

      

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