Cyber-Physical Construction Platform

Research Project 8-2 (RP 8-2)

Weiße Schrift

CYBER-PHYSICAL CONSTRUCTION PLATFORM

This project aims to extend the cyber-physical construction platform of project phase 1 consisting of a tower crane with image-based sensor network, spider crane and both platforms’ novel gripper systems in order to autonomously perform trustworthy georeferenced assembly tasks in absolute coordinates. Throughout project phase 1, the tower crane was automated enabling georeferenced positioning in absolute coordinates for payloads with the tower crane as a stand-alone system. Moreover, a gripper was developed that is able to incline attached payloads in two directions. To achieve automated assembly, the next step is to realize autonomous load pick up, extend the environmental sensing capabilities to highly dynamic environments allowing to evade dynamic obstacles during transportation and to investigate collaborative assembly for the tower and spider crane collaboration which is supported by the image-based sensing system. For the autonomous pick up, the gripper developed in phase 1 is extended to be able to pick up elements without human interaction. The to-be-transported prefabricated element is identified with image sensors. Afterwards, the crane picks the element up considering dynamic contact situations. For the environmental sensing, methods to derive an environmental model of the construction site that shows the current state in real-time will be in focus. This enables to investigate evasion strategies once a dynamic obstacles interferes the currently planned path. For the assembly, we extend the collaboration of tower and spider crane to assembly processes. For the tower crane, the crucial research topic is the rope-guided collaborative assembly, i.e. the rope guided handling of payloads while taking contact forces between manipulator and existing building stock parts into account. The image-based sensor network is integrated into the assembly process by reconstructing occluded areas covered by the transported prefabricated element and tracking the surrounding of the payload.

The intended automated assembly subprocesses will be shaped by distributed, discontinuous, and potentially fragmented interactions between various objects and human operators [12, 13,14].This type of increased ‘interobjectivity’ between objects such as the tower crane, spider crane, mobile fabrication platform and mobile robots within cyber-physical construction systems (CPCS) [12, 14]raises social science questions regarding the controllability and trustworthiness of CPCS as well as the relationship of automation and accountability [15]. Therefore, we will examine the requirements of trust(worthiness) from the perspective of the human machine operators as well as the contracting organizations: What are the prerequisites for trust in automated, hybrid technology and the related socio-technical systems? Is specific knowledge required to control a cyber-physical construction platform and to avoid situations of risk? Starting with three levels of trust building (human-machine-interaction, organization, sociotechnical systems) we highlight their relative importance, integration and competence requirements. By examining the conditions of a responsible and socially robust work situation in CPCS [10, 16], we aim to contribute to a socially sustainable and future-proof building culture.

[10] C. Kropp, “Hybride Kontrolle” in F. Sprenger (ed.), Autonome Autos. Medien- und kulturwissenschaftliche Perspektiven auf die Zukunft der Mobilität, transcript, Bielefeld, pp. 85-116, 2021.
[12] Rammert, “Technik – Handeln – Wissen. Zu einer pragmatistischen Technik- und Sozialtheorie,“ Springer VS, Wiesbaden, 2016.
[13] B. Whitworth, “A Brief Introduction to Sociotechnical Systems,” in IGI Global (eds.). Encyclopedia of Information Science and Technology, Second Edition, pp. 394–400, 2009.
[14] G. Sammut, F. Moghaddam, „Interobjectivity,“ in T.Teo (eds.) Encyclopedia of Critical Psychology, Springer, New York.
[15] Saurwein, “Emerging structures of control for algorithms on the internet. Distributed agency – distributed accountability” in T. Eberwein, S. Fengler, and M. Karmasin (eds.), Media Accountability in the era of posttruth politics, Routledge, London, pp. 196-211, 2019.
[16] N. Huchler, L. Adolph,  E. André, W. Bauer, N. Bender,  N. Müller, R. Neuburger, M. Peissner, J. Steil, S. Stowasser, and O. Suchy, “Kriterien für die menschengerechte Gestaltung der Mensch-Maschine-Interaktion bei Lernenden Systemen,” Whitepaper aus der Plattform Lernende Systeme, München, 2020

 

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
Prof. Dr. phil. Cordula Kropp
Institute for Social Sciences (SOWI), University of Stuttgart

TEAM

apl. Prof. Dr.-Ing. Norbert Haala (IFP)
Dr.-Ing. Johannes Schüle (ISYS)
Mark Burkhardt (ISYS)
Lena Joachim (IFP)
Michael Cramer (IFP)
Philipp Arnold (ISYS)
Ann-Kathrin Wortmeier (SOWI)
Amelie Schreck (SOWI)

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. 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
  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. 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. 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

DATA SETS

      

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