Robotic Platform for Cyber-Physical Assembly

Research Project 16-1 (RP 16-1)

ROBOTIC PLATFORM FOR CYBER-PHYSICAL ASSEMBLY OF LONG-SPAN FIBRE-COMPOSITE STRUCTURES

This research project addresses the development of a cyber-physical on-site construction platform for high-performance long-span buildings. The long-term goal is to automate material handling and on-site assembly of pre-fabricated fibre-composite elements using a ground-based, medium-payload, mobile, robotic boom manipulator. The team has the expertise needed to reach this goal by achieving interdisciplinary advances in cyber-physical construction platform design, sensor selection and real-time signal processing, algorithms for motion control, robot gripper design, and human-machine interaction.

On the one hand autonomous construction presupposes that control decisions are made in reaction to rich sensory input. To this end a real-time robot total station network will be installed on the construction site to locate the assembly robot at any time; this precise and robust system for measuring absolute position will enable automation of robot motion and building assembly as well as status monitoring of building elements. Complementary robot-fixed sensor systems will support detailed physical observation of the construction progress and (together with Research Project 8 (Cyber-Physical Construction Platform) monitoring of the condition of building elements. The robot will use all this information to perform relatively simple task steps autonomously. On the other hand, to allow for integration into a wide number of complex assembly processes and handle any problems that arise, we will create an intuitive haptic user interface that allows an on-site human operator to directly control the motion of the robot when needed. Haptic feedback from the robot’s sensors will enable the operator (and later the robot itself) to respond appropriately to physical contact during the assembly process, while cues from the structure’s digital model will virtually guide execution of the present task step.

Overall, this project aims to create a cyber-physical construction platform that can precisely place large building elements without damaging the building structure. We believe robotic automation based on precise localization and haptic feedback will speed up assembly and lead to a more efficient and correct construction process. Together with Research Project 8, this research project contributes significantly to the demonstrator by developing one of the IntCDC Instrumentation Platforms.

 

PRINCIPAL INVESTIGATORS

Dr. Katherine J. Kuchenbecker
Haptic Intelligence Department (MPI HI), Max Planck Institute for Intelligent Systems
Prof. Dr.-Ing. Dr. h.c. Oliver Sawodny
Institute for System Dynamics (ISYS), University of Stuttgart
Prof. Dr.-Ing. habil. Volker Schwieger
Institute of Engineering Geodesy (IIGS), University of Stuttgart

TEAM

Dr.-Ing. Otto Lerke (IIGS)
Dr. Bernard Javot (MPI)
Yijie Gong (MPI)
Anja Lauer (ISYS)
Mayumi Mohan (MPI)
Natalia Sanchez-Tamayo (MPI)
Naomi Tashiro (MPI)

 

PEER-REVIEWED PUBLICATIONS

  1. 2024

    1. Gienger, A., Stein, C., Lauer, A. P. R., Sawodny, O., & Tarín, C. (2024). Data-Based Reachability Analysis and Optimized Robot Positioning for Co-Design of Construction Processes. 2024 IEEE/SICE International Symposium on System Integration (SII).

  2. 2023

    1. Gong, Y., Javot, B., Lauer, A. P. R., Sawodny, O., & Kuchenbecker, K. J. (2023). Naturalistic Vibrotactile Feedback Could Facilitate Telerobotic Assembly on Construction Sites. In 2023 IEEE World Haptics Conference Committee (Ed.), 2023 IEEE World Haptics Conference (WHC) (pp. 169–175). https://doi.org/10.1109/WHC56415.2023.10224499
    2. Lauer, A. P. R., Benner, E., Stark, T., Klassen, S., Abolhasani, S., Schroth, L., Gienger, A., Wagner, H. J., Schwieger, V., Menges, A., & Sawodny, O. (2023). Automated on-site assembly of timber buildings on the example of a biomimetic shell. Automation in Construction.
    3. Lauer, A. P. R., Lerke, O., Blagojevic, B., Schwieger, V., & Sawodny, O. (2023). Tool Center Point Control of a Large-Scale Manipulator Using Absolute Position Feedback. Control Engineering Practice.
    4. Lauer, A. P. R., Lerke, O., Gienger, A., Schwieger, V., & Sawodny, O. (2023). State Estimation with Static Displacement Compensation for Large-Scale Manipulators. SII Atlanta.
    5. Lauer, A. P. R., Schürmann, T., Gienger, A., & Sawodny, O. (2023). Force-Controlled On-Site Assembly using Pose-Dependent Stiffness of Large-Scale Manipulators. Proceedings of the 2023 IEEE 19th International Conference on Automation Science and Engineering (CASE).
    6. Müller, B., Densborn, S., Kübel, J., & Sawodny, O. (2023). Smooth Path Planning for Redundant Large-Scale Robots using Measured Reference Points. Proceedings of The 22nd World Congress of the International Federation of Automatic Control (IFAC).

  3. 2022

    1. Burns, R. B., Lee, H., Seifi, H., Faulkner, R., & Kuchenbecker, K. J. (2022). Endowing a NAO Robot With Practical Social-Touch Perception. Frontiers in Robotics and AI, 9. https://doi.org/10.3389/frobt.2022.840335
    2. Oberdorfer, M., & Sawodny, O. (2022). Modeling and flatness based feedforward control of a hydraulic axial piston pump. Proceedings of the 2022 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM). https://doi.org/10.1109/AIM52237.2022.9863384
    3. Ortenzi, V., Filipovica, M., Abdlkarim, D., Pardi, T., Takahashi, C., Wing, A. M., Di Luca, M., & Kuchenbecker, K. J. (2022). Robot, Pass Me the Tool: Handle Visibility Facilitates Task-oriented Handovers. 2022 17th ACM/IEEE International Conference on Human-Robot Interaction (HRI), 256–264. https://doi.org/10.1109/HRI53351.2022.9889546
    4. Parlapanis, C., Müller, D., Frontull, M., & Sawodny, O. (2022). Modeling the Driving Dynamics of a Hydraulic Construction Vehicle. Proceedings of the 9th IFAC Symposium on Mechatronic Systems (Mechatronics 2022).
    5. Parlapanis, C., Müller, D., Frontull, M., & Sawodny, O. (2022). Modeling of the Work Functionality of a Hydraulically Actuated Telescopic Handler. IFAC-PapersOnLine, 55(20), Article 20.

  4. 2021

    1. Abdlkarim, D., Ortenzi, V., Pardi, T., Filipovica, M., Wing, A., Kuchenbecker, K., & Di Luca, M. (2021). PrendoSim: Proxy-Hand-Based Robot Grasp Generator. Proceedings of the 18th International Conference on Informatics in Control, Automation and Robotics - ICINCO, 60–68. https://doi.org/10.5220/0010549800600068
    2. Lauer, A. P. R., Blagojevic, B., Lerke, O., Schwieger, V., & Sawodny, O. (2021). Flexible Multibody System Model of a Spider Crane with two Extendable Booms. Proceedings of the 47th Annual Conference on the IEEE Industrial Electronics Society (IECON).
    3. Lerke, O., & Schwieger, V. (2021). Analysis of a kinematic real-time robotic total station network for robot control. Journal of Applied Geodesy, 15(3), Article 3. https://doi.org/doi:10.1515/jag-2021-0016
    4. Oei, M., & Sawodny, O. (2021). Attitude estimation for ground vehicles using low-cost sensors with in-vehicle calibration.
    5. Rupp, M. T. M., Valder, R., Knoll, C., & Sawodny, O. (2021). Cascaded Time Delay Compensation and Sensor Data Fusion for Visual Servoing.

  5. 2019

    1. Schwieger, V., Menges, A., Zhang, L., & Schwinn, T. (2019). Engineering Geodesy for Integrative Computational Design and Construction. Zeitschrift Für Geodäsie, Geoinformation Und Landmanagement (ZfV), 144(4), Article 4. https://doi.org/10.12902/zfv-0272-2019

OTHER PUBLICATIONS

  1. 2022

    1. Schwieger, V., Zhang, L., Lerke, O., & Balangé, L. (2022). The Research Cluster Integrative Computational Design and Construction (IntCDC) – Current Engineering Geodetic Contribution. XXVII FIG Congress 2022, Warsaw, Poland.

DATA SETS

  1. 2023

    1. Gong, Y., Javot, B., Lauer, A. P. R., Sawodny, O., & Kuchenbecker, K. J. (2023). User Study Dataset for Understanding On-Site Construction Activities with Haptic Perception. Edmond. https://doi.org/10.17617/3.PAFGCA

  2. 2022

    1. Burns, R. B., Lee, H., Seifi, H., Faulkner, R., & Kuchenbecker, K. J. (2022). User Study Dataset for Endowing a NAO Robot with Practical Social-Touch Perception. Edmond. https://doi.org/10.17617/3.6w
    2. Burns, R. B., Lee, H., Seifi, H., Faulkner, R., & Kuchenbecker, K. J. (2022). Sensor Patterns Dataset for Endowing a NAO Robot with Practical Social-Touch Perception. Edmond. https://doi.org/10.17617/3.6x

  

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